Intelligent Notification Systems: A Survey of the State of the Art and Research Challenges
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paper_title: I've got 99 problems, but vibration ain't one: a survey of smartphone users' concerns

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Smartphone operating systems warn users when third-party applications try to access sensitive functions or data. However, all of the major smartphone platforms warn users about different application actions. To our knowledge, their selection of warnings was not grounded in user research; past research on mobile privacy has focused exclusively on the risks pertained to sharing location. To expand the scope of smartphone security and privacy research, we surveyed 3,115 smartphone users about 99 risks associated with 54 smartphone privileges. We asked participants to rate how upset they would be if given risks occurred and used this data to rank risks by levels of user concern. We then asked 41 smartphone users to discuss the risks in their own words; their responses confirmed that people find the lowest-ranked risks merely annoying but might seek legal or financial retribution for the highest-ranked risks. In order to determine the relative frequency of risks, we also surveyed the 3,115 users about experiences with "misbehaving" applications. Our ranking and frequency data can be used to guide the selection of warnings on smartphone platforms.
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paper_title: Effects of Content and Time of Delivery on Receptivity to Mobile Interruptions

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In this paper we investigate effects of the content of interruptions and of the time of interruption delivery on mobile phones. We review related work and report on a naturalistic quasi-experiment using experience-sampling that showed that the receptivity to an interruption is influenced by its content rather than by its time of delivery in the employed modality of delivery - SMS. We also examined the underlying variables that increase the perceived quality of content and found that the factors interest, entertainment, relevance and actionability influence people's receptivity significantly. Our findings inform system design that seeks to provide context-sensitive information or to predict interruptibility and suggest the consideration of receptivity as an extension to the way we think and reason about interruptibility.
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paper_title: Designing content-driven intelligent notification mechanisms for mobile applications

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An increasing number of notifications demanding the smartphone user's attention, often arrive at an inappropriate moment, or carry irrelevant content. In this paper we present a study of mobile user interruptibility with respect to notification content, its sender, and the context in which a notification is received. In a real-world study we collect around 70,000 instances of notifications from 35 users. We group notifications according to the applications that initiated them, and the social relationship between the sender and the receiver. Then, by considering both content and context information, such as the current activity of a user, we discuss the design of classifiers for learning the most opportune moment for the delivery of a notification carrying a specific type of information. Our results show that such classifiers lead to a more accurate prediction of users' interruptibility than an alternative approach based on user-defined rules of their own interruptibility.
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paper_title: My Phone and Me: Understanding People's Receptivity to Mobile Notifications

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Notifications are extremely beneficial to users, but they often demand their attention at inappropriate moments. In this paper we present an in-situ study of mobile interruptibility focusing on the effect of cognitive and physical factors on the response time and the disruption perceived from a notification. Through a mixed method of automated smartphone logging and experience sampling we collected 10372 in-the-wild notifications and 474 questionnaire responses on notification perception from 20 users. We found that the response time and the perceived disruption from a notification can be influenced by its presentation, alert type, sender-recipient relationship as well as the type, completion level and complexity of the task in which the user is engaged. We found that even a notification that contains important or useful content can cause disruption. Finally, we observe the substantial role of the psychological traits of the individuals on the response time and the disruption perceived from a notification.
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paper_title: Large-scale assessment of mobile notifications

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Notifications are a core feature of mobile phones. They inform users about a variety of events. Users may take immediate action or ignore them depending on the importance of a notification as well as their current context. The nature of notifications is manifold, applications use them both sparsely and frequently. In this paper we present the first large-scale analysis of mobile notifications with a focus on users' subjective perceptions. We derive a holistic picture of notifications on mobile phones by collecting close to 200 million notifications from more than 40,000 users. Using a data-driven approach, we break down what users like and dislike about notifications. Our results reveal differences in importance of notifications and how users value notifications from messaging apps as well as notifications that include information about people and events. Based on these results we derive a number of findings about the nature of notifications and guidelines to effectively use them.
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paper_title: The Scope and Importance of Human Interruption in Human-Computer Interaction Design

paper_content:

At first glance it seems absurd that busy people doing important jobs should want their computers to interrupt them. Interruptions are disruptive and people need to concentrate to make good decisions. However, successful job performance also frequently depends on people's abilities to (a) constantly monitor their dynamically changing information environments, (b) collaborate and communicate with other people in the system, and (c) supervise background autonomous services. These critical abilities can require people to simultaneously query a large set of information sources, continuously monitor for important events, and respond to and communicate with other human operators. Automated monitoring and alerting systems minimize the need to constantly monitor, but they induce alerts that may interrupt other activities. Such interrupting technologies are already widespread and include concurrent multitasking; mixed-initiative interaction; support for delegation and supervisory control of automation, including intelligent agents; and other distributed, background services and technologies that increase human-human communication. ::: ::: People do not perform sustained, simultaneous, multichannel sampling well; however, they have great capacity to manage concurrent activities when given specific kinds of interface support. Literature from many domains shows deleterious consequences of human performance in interrupt-laden situations when interfaces do not support this aspect of the task environment. This article identifies why human interruption is an important human-computer interaction problem, and why it will continue to grow in ubiquity and importance. We provide examples of this problem in real-world systems, and we review theoretical tools for understanding human interruption. Based on interdisciplinary scientific results, we suggest potential approaches to user-interface design to help people effectively manage interruptions.
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paper_title: A model for notification systems evaluation—assessing user goals for multitasking activity

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Addressing the need to tailor usability evaluation methods (UEMs) and promote effective reuse of HCI knowledge for computing activities undertaken in divided-attention situations, we present the foundations of a unifying model that can guide evaluation efforts for notification systems. Often implemented as ubiquitous systems or within a small portion of the traditional desktop, notification systems typically deliver information of interest in a parallel, multitasking approach, extraneous or supplemental to a user's attention priority. Such systems represent a difficult challenge to evaluate meaningfully. We introduce a design model of user goals based on blends of three critical parameters---interruption, reaction, and comprehension. Categorization possibilities form a logical, descriptive design space for notification systems, rooted in human information processing theory. This model allows conceptualization of distinct action models for at least eight classes of notification systems, which we describe and analyze with a human information processing model. System classification regions immediately suggest useful empirical and analytical evaluation metrics from related literature. We present a case study that demonstrates how these techniques can assist an evaluator in adapting traditional UEMs for notification and other multitasking systems. We explain why using the design model categorization scheme enabled us to generate evaluation results that are more relevant for the system redesign than the results of the original exploration done by the system's designers.
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paper_title: Attention, Intentions, And The Structure Of Discourse

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In this paper we explore a new theory of discourse structure that stresses the role of purpose and processing in discourse. In this theory, discourse structure is composed of three separate but interrelated components: the structure of the sequence of utterances (called the linguistic structure), a structure of purposes (called the intentional structure), and the state of focus of attention (called the attentional state). The linguistic structure consists of segments of the discourse into which the utterances naturally aggregate. The intentional structure captures the discourse-relevant purposes, expressed in each of the linguistic segments as well as relationships among them. The attentional state is an abstraction of the focus of attention of the participants as the discourse unfolds. The attentional state, being dynamic, records the objects, properties, and relations that are salient at each point of the discourse. The distinction among these components is essential to provide an adequate explanation of such discourse phenomena as cue phrases, referring expressions, and interruptions.The theory of attention, intention, and aggregation of utterances is illustrated in the paper with a number of example discourses. Various properties of discourse are described, and explanations for the behavior of cue phrases, referring expressions, and interruptions are explored.This theory provides a framework for describing the processing of utterances in a discourse. Discourse processing requires recognizing how the utterances of the discourse aggregate into segments, recognizing the intentions expressed in the discourse and the relationships among intentions, and tracking the discourse through the operation of the mechanisms associated with attentional state. This processing description specifies in these recognition tasks the role of information from the discourse and from the participants' knowledge of the domain.
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paper_title: A simplest systematics for the organization of turn-taking for conversation

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Publisher Summary Turn taking is used for the ordering of moves in games, for allocating political office, for regulating traffic at intersections, for the servicing of customers at business establishments, and for talking in interviews, meetings, debates, ceremonies, conversations. This chapter discusses the turn-taking system for conversation. On the basis of research using audio recordings of naturally occurring conversations, the chapter highlights the organization of turn taking for conversation and extracts some of the interest that organization has. The turn-taking system for conversation can be described in terms of two components and a set of rules. These two components are turn-constructional component and turn-constructional component. Turn-allocational techniques are distributed into two groups: (1) those in which next turn is allocated by current speaker selecting a next speaker and (2) those in which next turn is allocated by self-selection. The turn-taking rule-set provides for the localization of gap and overlap possibilities at transition-relevance places and their immediate environment, cleansing the rest of a turn's space of systematic bases for their possibility.
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paper_title: Contributing to Discourse

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For people to contribute to discourse, they must do more than utter the right sentence at the right time. The basic requirement is that they odd to their common ground in on orderly way. To do this, we argue, they try to establish for each utterance the mutual belief that the addressees hove understood what the speaker meant well enough for current purposes. This is accomplished by the collective actions of the current contributor and his or her partners, and these result in units of conversation called contributions. We present a model of contributions and show how it accounts for o variety of features of everyday conversations. People take part in conversation in order to plan, debate, discuss, gossip, and carry out other social processes. When they do take part, they could be said to contribute to the discourse. But how do they contribute? At first the answer seems obvious. A discourse is a sequence of utterances produced as the participants proceed turn by turn. All that participants have to do to contribute is utter the right sentence at the right time. They may make errors, but once they have corrected them, they are done. The other participants have merely to listen and understand. This is the view subscribed to in most discourse theories in psychology, linguistics, philosophy; and artificial intelligence. A closer look at actual conversations, however, suggests that they are much more than sequences of utterances produced turn by turn. They are highly coordinated activities in which the current speaker tries to make sure he or she is being attended to, heard, and understood by the other participants, and they in turn try to let the speaker know when he or she has succeeded. Contributing to a discourse, then, appears to require more than just uttering the right words at the right time. It seems to consist of collective acts performed by the participants working together. In this paper we describe a model of contributions as parts of collective acts. We first describe the need for such a model, next present the model
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paper_title: Bluetooth and WAP push based location-aware mobile advertising system

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Advertising on mobile devices has large potential due to the very personal and intimate nature of the devices and high targeting possibilities. We introduce a novel B-MAD system for delivering permission-based location-aware mobile advertisements to mobile phones using Bluetooth positioning and Wireless Application Protocol (WAP) Push. We present a thorough quantitative evaluation of the system in a laboratory environment and qualitative user evaluation in form of a field trial in the real environment of use. Experimental results show that the system provides a viable solution for realizing permission-based mobile advertising.
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paper_title: The Scope and Importance of Human Interruption in Human-Computer Interaction Design

paper_content:

At first glance it seems absurd that busy people doing important jobs should want their computers to interrupt them. Interruptions are disruptive and people need to concentrate to make good decisions. However, successful job performance also frequently depends on people's abilities to (a) constantly monitor their dynamically changing information environments, (b) collaborate and communicate with other people in the system, and (c) supervise background autonomous services. These critical abilities can require people to simultaneously query a large set of information sources, continuously monitor for important events, and respond to and communicate with other human operators. Automated monitoring and alerting systems minimize the need to constantly monitor, but they induce alerts that may interrupt other activities. Such interrupting technologies are already widespread and include concurrent multitasking; mixed-initiative interaction; support for delegation and supervisory control of automation, including intelligent agents; and other distributed, background services and technologies that increase human-human communication. ::: ::: People do not perform sustained, simultaneous, multichannel sampling well; however, they have great capacity to manage concurrent activities when given specific kinds of interface support. Literature from many domains shows deleterious consequences of human performance in interrupt-laden situations when interfaces do not support this aspect of the task environment. This article identifies why human interruption is an important human-computer interaction problem, and why it will continue to grow in ubiquity and importance. We provide examples of this problem in real-world systems, and we review theoretical tools for understanding human interruption. Based on interdisciplinary scientific results, we suggest potential approaches to user-interface design to help people effectively manage interruptions.
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paper_title: Interruption of People in Human-Computer Interaction: A General Unifying Definition of Human Interruption and Taxonomy

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Abstract : User-interruption in human-computer interaction (HCI) is an increasingly important problem. Many of the useful advances in intelligent and multitasking computer systems have the significant side effect of greatly increasing user-interruption. This previously innocuous HCI problem has become critical to the successful function of many kinds of modern computer systems. Unfortunately, no HCI design guidelines exist for solving this problem. In fact, theoretical tools do not yet exist for investigating the HCI problem of user-interruption in a comprehensive and generalizable way. This report asserts that a single unifying definition of user-interruption and the accompanying practical taxonomy would be useful theoretical tools for driving effective investigation of this crucial HCI problem. These theoretical tools are constructed here. A comprehensive analysis is conducted through the existing literature. Theoretical constructs from several relevant but diverse fields are identified and discussed. A unifying definition of user-interruption is synthesized. This new definition is supported with an array of postulates, assertions, and a taxonomy of human interruption to facilitate its practical application.
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paper_title: Investigating Interruptions: Implications for Flightdeck Performance

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A fundamental aspect of multiple task management is attending to new stimuli and integrating associated task requirements into an ongoing task set; this is "interruption management" (IM). Anecdotal evidence and field studies indicate the frequency and consequences of interruptions, however experimental investigations of mechanisms influencing IM are scarce. Interruptions on commercial flightdecks are numerous, of various forms, and have been cited as contributing factors in many aviation incident and accident reports. This research grounds an experimental investigation of flight deck interruptions in a proposed IM stage model. This model organizes basic research, identifies influencing mechanisms, and suggests appropriate dependent measures for IM. Fourteen airline pilots participated in a flightdeck simulation experiment to investigate the general effects of performing an interrupting task and interrupted procedure, and the effects of specific task factors: (1) modality; (2) embeddedness, or goal-level, of an interruption; (3) strength of association, or coupling-strength, between interrupted tasks; (4) semantic similarity; and (5) environmental stress. General effects of interruptions were extremely robust. All individual task factors significantly affected interruption management, except "similarity." Results extend the Interruption Management model, and are interpreted for their implications for interrupted flightdeck performance and intervention strategies for mitigating their effects on the flightdeck.
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paper_title: Task Interruption and its Effects on Memory

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We investigated the recovery from memory of a primary task after an interruption. If the primary task lacked associative support among its task components, recovery was more difficult following an interruption that overlapped either completely or partially in the amount of information shared with the primary task (an interruption-similarity effect). In addition, memory for completed actions was superior to memory for impending unfinished actions. However, if the primary task had associative support among its task components, there was no adverse effect of interruption similarity, and completed and unfinished actions were recalled equally well. We explore possible explanations and implications of these results.
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paper_title: Notification, Disruption, and Memory: Effects of Messaging Interruptions on Memory and Performance

paper_content:

We describe a study on the influence of instant messaging (IM) on ongoing computing tasks. The study both replicates and extends earlier work on the cost of sending notifications at different times and the sensitivity of different tasks to interruption. We investigate alternative hypotheses about the nature of disruption for a list evaluation task, an activity identified as being particularly costly to interrupt. Our findings once again show the generally disruptive effects of IM, especially during fast, stimulus-driven search tasks. In addition, we show that interruptions coming early during a search task are more likely to result in the user forgetting the primary task goal than interruptions that arrive later on. These findings have implications for the design of user interfaces and notification policies that minimize the disruptiveness of notifications.
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paper_title: Measuring the effects of interruptions on task performance in the user interface

paper_content:

As users continue offloading more control and responsibility to the computer, coordinating the asynchronous interactions between the user and computer is becoming increasingly important. Without proper coordination, an application attempting to gain the user's attention risks interrupting the user in the midst of performing another task. To justify why an application should avoid interrupting the user whenever possible, we designed an experiment measuring the disruptive effect of an interruption on a user's task performance. The experiment utilized six Web-based task categories and two categories of interruption tasks. The results of the experiment demonstrate that: (i) a user performs slower on an interrupted task than a non-interrupted task, (ii) the disruptive effect of an interruption differs as a function of the task category, and (iii) different interruption tasks cause similar disruptive effects on task performance. These results empirically validate the need to better coordinate user interactions among applications that are competing for the user's attention.
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paper_title: Creativity and sensory gating indexed by the P50: Selective versus leaky sensory gating in divergent thinkers and creative achievers

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Creativity has previously been linked with atypical attention, but it is not clear what aspects of attention, or what types of creativity are associated. Here we investigated specific neural markers of a very early form of attention, namely sensory gating, indexed by the P50 ERP, and how it relates to two measures of creativity: divergent thinking and real-world creative achievement. Data from 84 participants revealed that divergent thinking (assessed with the Torrance Test of Creative Thinking) was associated with se- lective sensory gating, whereas real-world creative achievement was associated with "leaky" sensory gating, both in zero-order correlations and when controlling for academic test scores in a regression. Thus both creativity measures related to sensory gating, but in opposite directions. Additionally, di- vergent thinking and real-world creative achievement did not interact in predicting P50 sensory gating, suggesting that these two creativity measures orthogonally relate to P50 sensory gating. Finally, the ERP effect was specific to the P50 - neither divergent thinking nor creative achievement were related to later components, such as the N100 and P200. Overall results suggest that leaky sensory gating may help people integrate ideas that are outside of focus of attention, leading to creativity in the real world; whereas divergent thinking, measured by divergent thinking tests which emphasize numerous re- sponses within a limited time, may require selective sensory processing more than previously thought. & 2015 Elsevier Ltd. All rights reserved.
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paper_title: Task Interruption and its Effects on Memory

paper_content:

We investigated the recovery from memory of a primary task after an interruption. If the primary task lacked associative support among its task components, recovery was more difficult following an interruption that overlapped either completely or partially in the amount of information shared with the primary task (an interruption-similarity effect). In addition, memory for completed actions was superior to memory for impending unfinished actions. However, if the primary task had associative support among its task components, there was no adverse effect of interruption similarity, and completed and unfinished actions were recalled equally well. We explore possible explanations and implications of these results.
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paper_title: The psychology of memory

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In this chapter I will try to provide a brief overview of the concepts and techniques that are most widely used in the psychology of memory. Although it may not appear to be the case from sampling the literature, there is in fact a great deal of agreement as to what constitutes the psychology of memory, much of it developed through the interaction of the study of normal memory in the laboratory and of its breakdown in brain-damaged patients. A somewhat more detailed account can be found in Parkin & Leng (1993) and Baddeley (1999), while a more extensive overview is given by Baddeley (1997), and within the various chapters comprising the Handbook of Memory (Tulving & Craik, 2000). THE FRACTIONATION OF MEMORY The concept of human memory as a unitary faculty began to be seriously eroded in the 1960s with the proposal that long-term memory (LTM) and short-term memory (STM) represent separate systems. Among the strongest evidence for this dissociation was the contrast between two types of neuropsychological patient. Patients with the classic amnesic syndrome, typically associated with damage to the temporal lobes and hippocampi, appeared to have a quite general problem in learning and remembering new material, whether verbal or visual (Milner, 1966). They did, however, appear to have normal short-term memory (STM), as measured for example by digit span, the capacity to hear and immediately repeat back a unfamiliar sequence of numbers. Shallice & Warrington (1970) identified an exactly opposite pattern of deficit in patients with damage to the perisylvian region of the left hemisphere. Such patients had a digit span limited to one or two, but apparently normal LTM. By the late 1960s, the evidence seemed to be pointing clearly to a two-component memory system. Figure 1.1 shows the representation of such a system from an influential model of the time, that of Atkinson & Shiffrin (1968). Information is assumed to flow from the environment through a series of very brief sensory memories, that are perhaps best regarded as part of the perceptual system, into a limited capacity short-term store. They proposed that the longer an item resides in this store, the greater the probability of its transfer to LTM. Amnesic patients were assumed to have a deficit in the LTM system, and STM patients in the short-term store.
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paper_title: Instant Messaging and Interruption : Influence of Task Type on Performance

paper_content:

We describe research on the effects of instant messaging (IM) on ongoing computing tasks. We present a study that builds on earlier work exploring the influence of sending notifications at different times and the kinds of tasks that are particularly susceptible to interruption. This work investigates alternative hypotheses about the nature of disruption for a list evaluation task, an activity we had identified as being particularly costly to interrupt. Our findings replicate earlier work, showing the generally harmful effects of IM, and further show that notifications are more disruptive for fast, stimulus-driven search tasks than for slower, more effortful semantic-based search tasks.
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paper_title: Interruption as a test of the user-computer interface

paper_content:

In order to study the effects different logic systems might have on interrupted operation, an algebraic calculator and a reverse polish notation calculator were compared when trained users were interrupted during problem entry. The RPN calculator showed markedly superior resistance to interruption effects compared to the AN calculator although no significant differences were found when the users were not interrupted. Causes and possible remedies for interruption effects are speculated. It is proposed that because interruption is such a common occurrence, it be incorporated into comparative evaluation tests of different logic system and control/display system and that interruption resistance be adopted as a specific design criteria for such design.
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paper_title: Notification, Disruption, and Memory: Effects of Messaging Interruptions on Memory and Performance

paper_content:

We describe a study on the influence of instant messaging (IM) on ongoing computing tasks. The study both replicates and extends earlier work on the cost of sending notifications at different times and the sensitivity of different tasks to interruption. We investigate alternative hypotheses about the nature of disruption for a list evaluation task, an activity identified as being particularly costly to interrupt. Our findings once again show the generally disruptive effects of IM, especially during fast, stimulus-driven search tasks. In addition, we show that interruptions coming early during a search task are more likely to result in the user forgetting the primary task goal than interruptions that arrive later on. These findings have implications for the design of user interfaces and notification policies that minimize the disruptiveness of notifications.
---
paper_title: Measuring the effects of interruptions on task performance in the user interface

paper_content:

As users continue offloading more control and responsibility to the computer, coordinating the asynchronous interactions between the user and computer is becoming increasingly important. Without proper coordination, an application attempting to gain the user's attention risks interrupting the user in the midst of performing another task. To justify why an application should avoid interrupting the user whenever possible, we designed an experiment measuring the disruptive effect of an interruption on a user's task performance. The experiment utilized six Web-based task categories and two categories of interruption tasks. The results of the experiment demonstrate that: (i) a user performs slower on an interrupted task than a non-interrupted task, (ii) the disruptive effect of an interruption differs as a function of the task category, and (iii) different interruption tasks cause similar disruptive effects on task performance. These results empirically validate the need to better coordinate user interactions among applications that are competing for the user's attention.
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paper_title: If not now, when?: the effects of interruption at different moments within task execution

paper_content:

User attention is a scarce resource, and users are susceptible to interruption overload. Systems do not reason about the effects of interrupting a user during a task sequence. In this study, we measure effects of interrupting a user at different moments within task execution in terms of task performance, emotional state, and social attribution. Task models were developed using event perception techniques, and the resulting models were used to identify interruption timings based on a user's predicted cognitive load. Our results show that different interruption moments have different impacts on user emotional state and positive social attribution, and suggest that a system could enable a user to maintain a high level of awareness while mitigating the disruptive effects of interruption. We discuss implications of these results for the design of an attention manager.
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paper_title: "Silence Your Phones": Smartphone Notifications Increase Inattention and Hyperactivity Symptoms

paper_content:

As smartphones increasingly pervade our daily lives, people are ever more interrupted by alerts and notifications. Using both correlational and experimental methods, we explored whether such interruptions might be causing inattention and hyperactivity-symptoms associated with Attention Deficit Hyperactivity Disorder (ADHD) even in people not clinically diagnosed with ADHD. We recruited a sample of 221 participants from the general population. For one week, participants were assigned to maximize phone interruptions by keeping notification alerts on and their phones within their reach/sight. During another week, participants were assigned to minimize phone interruptions by keeping alerts off and their phones away. Participants reported higher levels of inattention and hyperactivity when alerts were on than when alerts were off. Higher levels of inattention in turn predicted lower productivity and psychological well-being. These findings highlight some of the costs of ubiquitous connectivity and suggest how people can reduce these costs simply by adjusting existing phone settings.
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paper_title: Task Interruption and its Effects on Memory

paper_content:

We investigated the recovery from memory of a primary task after an interruption. If the primary task lacked associative support among its task components, recovery was more difficult following an interruption that overlapped either completely or partially in the amount of information shared with the primary task (an interruption-similarity effect). In addition, memory for completed actions was superior to memory for impending unfinished actions. However, if the primary task had associative support among its task components, there was no adverse effect of interruption similarity, and completed and unfinished actions were recalled equally well. We explore possible explanations and implications of these results.
---
paper_title: Interruption as a test of the user-computer interface

paper_content:

In order to study the effects different logic systems might have on interrupted operation, an algebraic calculator and a reverse polish notation calculator were compared when trained users were interrupted during problem entry. The RPN calculator showed markedly superior resistance to interruption effects compared to the AN calculator although no significant differences were found when the users were not interrupted. Causes and possible remedies for interruption effects are speculated. It is proposed that because interruption is such a common occurrence, it be incorporated into comparative evaluation tests of different logic system and control/display system and that interruption resistance be adopted as a specific design criteria for such design.
---
paper_title: Notification, Disruption, and Memory: Effects of Messaging Interruptions on Memory and Performance

paper_content:

We describe a study on the influence of instant messaging (IM) on ongoing computing tasks. The study both replicates and extends earlier work on the cost of sending notifications at different times and the sensitivity of different tasks to interruption. We investigate alternative hypotheses about the nature of disruption for a list evaluation task, an activity identified as being particularly costly to interrupt. Our findings once again show the generally disruptive effects of IM, especially during fast, stimulus-driven search tasks. In addition, we show that interruptions coming early during a search task are more likely to result in the user forgetting the primary task goal than interruptions that arrive later on. These findings have implications for the design of user interfaces and notification policies that minimize the disruptiveness of notifications.
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paper_title: Human Computer Interaction

paper_content:

Contents Foreword Preface to the third edition Preface to the second edition Preface to the first edition Introduction Part 1 Foundations Chapter 1 The human 1.1 Introduction 1.2 Input-output channels Design Focus: Getting noticed Design Focus: Where's the middle? 1.3 Human memory Design Focus: Cashing in Design Focus: 7 +- 2 revisited 1.4 Thinking: reasoning and problem solving Design Focus: Human error and false memories 1.5 Emotion 1.6 Individual differences 1.7 Psychology and the design of interactive systems 1.8 Summary Exercises Recommended reading Chapter 2 The computer 2.1 Introduction Design Focus: Numeric keypads 2.2 Text entry devices 2.3 Positioning, pointing and drawing 2.4 Display devices Design Focus: Hermes: a situated display 2.5 Devices for virtual reality and 3D interaction 2.6 Physical controls, sensors and special devices Design Focus: Feeling the road Design Focus: Smart-Its - making sensors easy 2.7 Paper: printing and scanning Design Focus: Readability of text 2.8 Memory 2.9 Processing and networks Design Focus: The myth of the infinitely fast machine 2.10 Summary Exercises Recommended reading Chapter 3 The interaction 3.1 Introduction 3.2 Models of interaction Design Focus: Video recorder 3.3 Frameworks and HCI 3.4 Ergonomics Design Focus: Industrial interfaces 3.5 Interaction styles Design Focus: Navigation in 3D and 2D 3.6 Elements of the WIMP interface Design Focus: Learning toolbars 3.7 Interactivity 3.8 The context of the interaction Design Focus: Half the picture? 3.9 Experience, engagement and fun 3.10 Summary Exercises Recommended reading Chapter 4 Paradigms 4.1 Introduction 4.2 Paradigms for interaction 4.3 Summary Exercises Recommended reading Part 2 Design process Chapter 5 Interaction design basics 5.1 Introduction 5.2 What is design? 5.3 The process of design 5.4 User focus Design Focus: Cultural probes 5.5 Scenarios 5.6 Navigation design Design Focus: Beware the big button trap Design Focus: Modes 5.7 Screen design and layout Design Focus: Alignment and layout matter Design Focus: Checking screen colors 5.8 Iteration and prototyping 5.9 Summary Exercises Recommended reading Chapter 6 HCI in the software process 6.1 Introduction 6.2 The software life cycle 6.3 Usability engineering 6.4 Iterative design and prototyping Design Focus: Prototyping in practice 6.5 Design rationale 6.6 Summary Exercises Recommended reading Chapter 7 Design rules 7.1 Introduction 7.2 Principles to support usability 7.3 Standards 7.4 Guidelines 7.5 Golden rules and heuristics 7.6 HCI patterns 7.7 Summary Exercises Recommended reading Chapter 8 Implementation support 8.1 Introduction 8.2 Elements of windowing systems 8.3 Programming the application Design Focus: Going with the grain 8.4 Using toolkits Design Focus: Java and AWT 8.5 User interface management systems 8.6 Summary Exercises Recommended reading Chapter 9 Evaluation techniques 9.1 What is evaluation? 9.2 Goals of evaluation 9.3 Evaluation through expert analysis 9.4 Evaluation through user participation 9.5 Choosing an evaluation method 9.6 Summary Exercises Recommended reading Chapter 10 Universal design 10.1 Introduction 10.2 Universal design principles 10.3 Multi-modal interaction Design Focus: Designing websites for screen readers Design Focus: Choosing the right kind of speech Design Focus: Apple Newton 10.4 Designing for diversity Design Focus: Mathematics for the blind 10.5 Summary Exercises Recommended reading Chapter 11 User support 11.1 Introduction 11.2 Requirements of user support 11.3 Approaches to user support 11.4 Adaptive help systems Design Focus: It's good to talk - help from real people 11.5 Designing user support systems 11.6 Summary Exercises Recommended reading Part 3 Models and theories Chapter 12 Cognitive models 12.1 Introduction 12.2 Goal and task hierarchies Design Focus: GOMS saves money 12.3 Linguistic models 12.4 The challenge of display-based systems 12.5 Physical and device models 12.6 Cognitive architectures 12.7 Summary Exercises Recommended reading Chapter 13 Socio-organizational issues and stakeholder requirements 13.1 Introduction 13.2 Organizational issues Design Focus: Implementing workflow in Lotus Notes 13.3 Capturing requirements Design Focus: Tomorrow's hospital - using participatory design 13.4 Summary Exercises Recommended reading Chapter 14 Communication and collaboration models 14.1 Introduction 14.2 Face-to-face communication Design Focus: Looking real - Avatar Conference 14.3 Conversation 14.4 Text-based communication 14.5 Group working 14.6 Summary Exercises Recommended reading Chapter 15 Task analysis 15.1 Introduction 15.2 Differences between task analysis and other techniques 15.3 Task decomposition 15.4 Knowledge-based analysis 15.5 Entity-relationship-based techniques 15.6 Sources of information and data collection 15.7 Uses of task analysis 15.8 Summary Exercises Recommended reading Chapter 16 Dialog notations and design 16.1 What is dialog? 16.2 Dialog design notations 16.3 Diagrammatic notations Design Focus: Using STNs in prototyping Design Focus: Digital watch - documentation and analysis 16.4 Textual dialog notations 16.5 Dialog semantics 16.6 Dialog analysis and design 16.7 Summary Exercises Recommended reading Chapter 17 Models of the system 17.1 Introduction 17.2 Standard formalisms 17.3 Interaction models 17.4 Continuous behavior 17.5 Summary Exercises Recommended reading Chapter 18 Modeling rich interaction 18.1 Introduction 18.2 Status-event analysis 18.3 Rich contexts 18.4 Low intention and sensor-based interaction Design Focus: Designing a car courtesy light 18.5 Summary Exercises Recommended reading Part 4 Outside the box Chapter 19 Groupware 19.1 Introduction 19.2 Groupware systems 19.3 Computer-mediated communication Design Focus: SMS in action 19.4 Meeting and decision support systems 19.5 Shared applications and artifacts 19.6 Frameworks for groupware Design Focus: TOWER - workspace awareness Exercises Recommended reading Chapter 20 Ubiquitous computing and augmented realities 20.1 Introduction 20.2 Ubiquitous computing applications research Design Focus: Ambient Wood - augmenting the physical Design Focus: Classroom 2000/eClass - deploying and evaluating ubicomp 20.3 Virtual and augmented reality Design Focus: Shared experience Design Focus: Applications of augmented reality 20.4 Information and data visualization Design Focus: Getting the size right 20.5 Summary Exercises Recommended reading Chapter 21 Hypertext, multimedia and the world wide web 21.1 Introduction 21.2 Understanding hypertext 21.3 Finding things 21.4 Web technology and issues 21.5 Static web content 21.6 Dynamic web content 21.7 Summary Exercises Recommended reading References Index
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paper_title: Instant Messaging and Interruption : Influence of Task Type on Performance

paper_content:

We describe research on the effects of instant messaging (IM) on ongoing computing tasks. We present a study that builds on earlier work exploring the influence of sending notifications at different times and the kinds of tasks that are particularly susceptible to interruption. This work investigates alternative hypotheses about the nature of disruption for a list evaluation task, an activity we had identified as being particularly costly to interrupt. Our findings replicate earlier work, showing the generally harmful effects of IM, and further show that notifications are more disruptive for fast, stimulus-driven search tasks than for slower, more effortful semantic-based search tasks.
---
paper_title: Interruption as a test of the user-computer interface

paper_content:

In order to study the effects different logic systems might have on interrupted operation, an algebraic calculator and a reverse polish notation calculator were compared when trained users were interrupted during problem entry. The RPN calculator showed markedly superior resistance to interruption effects compared to the AN calculator although no significant differences were found when the users were not interrupted. Causes and possible remedies for interruption effects are speculated. It is proposed that because interruption is such a common occurrence, it be incorporated into comparative evaluation tests of different logic system and control/display system and that interruption resistance be adopted as a specific design criteria for such design.
---
paper_title: Notification, Disruption, and Memory: Effects of Messaging Interruptions on Memory and Performance

paper_content:

We describe a study on the influence of instant messaging (IM) on ongoing computing tasks. The study both replicates and extends earlier work on the cost of sending notifications at different times and the sensitivity of different tasks to interruption. We investigate alternative hypotheses about the nature of disruption for a list evaluation task, an activity identified as being particularly costly to interrupt. Our findings once again show the generally disruptive effects of IM, especially during fast, stimulus-driven search tasks. In addition, we show that interruptions coming early during a search task are more likely to result in the user forgetting the primary task goal than interruptions that arrive later on. These findings have implications for the design of user interfaces and notification policies that minimize the disruptiveness of notifications.
---
paper_title: Measuring the effects of interruptions on task performance in the user interface

paper_content:

As users continue offloading more control and responsibility to the computer, coordinating the asynchronous interactions between the user and computer is becoming increasingly important. Without proper coordination, an application attempting to gain the user's attention risks interrupting the user in the midst of performing another task. To justify why an application should avoid interrupting the user whenever possible, we designed an experiment measuring the disruptive effect of an interruption on a user's task performance. The experiment utilized six Web-based task categories and two categories of interruption tasks. The results of the experiment demonstrate that: (i) a user performs slower on an interrupted task than a non-interrupted task, (ii) the disruptive effect of an interruption differs as a function of the task category, and (iii) different interruption tasks cause similar disruptive effects on task performance. These results empirically validate the need to better coordinate user interactions among applications that are competing for the user's attention.
---
paper_title: If not now, when?: the effects of interruption at different moments within task execution

paper_content:

User attention is a scarce resource, and users are susceptible to interruption overload. Systems do not reason about the effects of interrupting a user during a task sequence. In this study, we measure effects of interrupting a user at different moments within task execution in terms of task performance, emotional state, and social attribution. Task models were developed using event perception techniques, and the resulting models were used to identify interruption timings based on a user's predicted cognitive load. Our results show that different interruption moments have different impacts on user emotional state and positive social attribution, and suggest that a system could enable a user to maintain a high level of awareness while mitigating the disruptive effects of interruption. We discuss implications of these results for the design of an attention manager.
---
paper_title: "Silence Your Phones": Smartphone Notifications Increase Inattention and Hyperactivity Symptoms

paper_content:

As smartphones increasingly pervade our daily lives, people are ever more interrupted by alerts and notifications. Using both correlational and experimental methods, we explored whether such interruptions might be causing inattention and hyperactivity-symptoms associated with Attention Deficit Hyperactivity Disorder (ADHD) even in people not clinically diagnosed with ADHD. We recruited a sample of 221 participants from the general population. For one week, participants were assigned to maximize phone interruptions by keeping notification alerts on and their phones within their reach/sight. During another week, participants were assigned to minimize phone interruptions by keeping alerts off and their phones away. Participants reported higher levels of inattention and hyperactivity when alerts were on than when alerts were off. Higher levels of inattention in turn predicted lower productivity and psychological well-being. These findings highlight some of the costs of ubiquitous connectivity and suggest how people can reduce these costs simply by adjusting existing phone settings.
---
paper_title: TIME-SHARING REVISITED: TEST OF A COMPONENTIAL MODEL FOR THE ASSESSMENT OF INDIVIDUAL DIFFERENCES

paper_content:

Abstract Time-sharing ability as an individual differences variable in dual task performance was examined using a componential model. Five proposed components were assessed: (1) serial processing ability; (2) an internal model of the system dynamics; (3) performing heterogeneous operations; (4) adaptation to rapidly changing dynamic conditions; (5) parallel processing ability. The approach combined methodologies from experimental psychology and from individual differences research. Forty subjects were given four single task pretests, and then performed a compensatory tracking task in various dual task combinations administered during six sessions over a period of three days. At the conclusion of the experiment the subjects had to perform three different dual task transfer tasks. The results of a factor analysis and a series of stepwise multiple-regression analyses revealed two important dimensions of individual differences in dual task performance: (1) individual differences in cognitive style linked to t...
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paper_title: Interruption of a Monotonous Activity with Complex Tasks: Effects of Individual Differences

paper_content:

The fluctuations of vigilance and performance for operators working in monotonous conditions were studied in laboratory. Three experimental designs were achieved on 20 subjects:—one reference condition with a vigilance task of 3 hours 30 during day time,—one experimental condition with interruptions of monotony during the vigilance task by a sustained task, during the same day time period,—the same experimental condition during night time.The purpose was to analyse the effect of breakdown in monotony on arousal and human performance and to look for individual differences in human performance. Physiological data were collected in order to study the variation of arousal. Response times and omissions were used as performance index. Individual differences can be observed for performance and vigilance. Two kinds of behavior are defined: stable subjects and subjects characterized by fluctuations both for arousal and performance during the task. During day time period, breakdown of monotony has a positive effect...
---
paper_title: Towards an index of opportunity: understanding changes in mental workload during task execution

paper_content:

To contribute to systems that reason about human attention, our work empirically demonstrates how a user's mental workload changes during task execution. We conducted a study where users performed interactive, hierarchical tasks while mental workload was measured through the use of pupil size. Results show that (i) different types of subtasks impose different mental workload, (ii) workload decreases at subtask boundaries, (iii) workload decreases more at boundaries higher in a task model and less at boundaries lower in the model, (iv) workload changes among subtask boundaries within the same level of a task model, and (v) effective understanding of why changes in workload occur requires that the measure be tightly coupled to a validated task model. From the results, we show how to map mental workload onto a computational Index of Opportunity that systems can use to better reason about human attention.
---
paper_title: Effects of Content and Time of Delivery on Receptivity to Mobile Interruptions

paper_content:

In this paper we investigate effects of the content of interruptions and of the time of interruption delivery on mobile phones. We review related work and report on a naturalistic quasi-experiment using experience-sampling that showed that the receptivity to an interruption is influenced by its content rather than by its time of delivery in the employed modality of delivery - SMS. We also examined the underlying variables that increase the perceived quality of content and found that the factors interest, entertainment, relevance and actionability influence people's receptivity significantly. Our findings inform system design that seeks to provide context-sensitive information or to predict interruptibility and suggest the consideration of receptivity as an extension to the way we think and reason about interruptibility.
---
paper_title: Didn't you see my message?: predicting attentiveness to mobile instant messages

paper_content:

Mobile instant messaging (e.g., via SMS or WhatsApp) often goes along with an expectation of high attentiveness, i.e., that the receiver will notice and read the message within a few minutes. Hence, existing instant messaging services for mobile phones share indicators of availability, such as the last time the user has been online. However, in this paper we not only provide evidence that these cues create social pressure, but that they are also weak predictors of attentiveness. As remedy, we propose to share a machine-computed prediction of whether the user will view a message within the next few minutes or not. For two weeks, we collected behavioral data from 24 users of mobile instant messaging services. By the means of machine-learning techniques, we identified that simple features extracted from the phone, such as the user's interaction with the notification center, the screen activity, the proximity sensor, and the ringer mode, are strong predictors of how quickly the user will attend to the messages. With seven automatically selected features our model predicts whether a phone user will view a message within a few minutes with 70.6% accuracy and a precision for fast attendance of 81.2%
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paper_title: Predicting human interruptibility with sensors: a Wizard of Oz feasibility study

paper_content:

A person seeking someone else's attention is normally able to quickly assess how interruptible they are. This assessment allows for behavior we perceive as natural, socially appropriate, or simply polite. On the other hand, today's computer systems are almost entirely oblivious to the human world they operate in, and typically have no way to take into account the interruptibility of the user. This paper presents a Wizard of Oz study exploring whether, and how, robust sensor-based predictions of interruptibility might be constructed, which sensors might be most useful to such predictions, and how simple such sensors might be.The study simulates a range of possible sensors through human coding of audio and video recordings. Experience sampling is used to simultaneously collect randomly distributed self-reports of interruptibility. Based on these simulated sensors, we construct statistical models predicting human interruptibility and compare their predictions with the collected self-report data. The results of these models, although covering a demographically limited sample, are very promising, with the overall accuracy of several models reaching about 78%. Additionally, a model tuned to avoiding unwanted interruptions does so for 90% of its predictions, while retaining 75% overall accuracy.
---
paper_title: Models of attention in computing and communication: from principles to applications

paper_content:

Creating computing and communication systems that sense and reason about human attention by fusing together information from multiple streams.
---
paper_title: Examining the robustness of sensor-based statistical models of human interruptibility

paper_content:

Current systems often create socially awkward interruptions or unduly demand attention because they have no way of knowing if a person is busy and should not be interrupted. Previous work has examined the feasibility of using sensors and statistical models to estimate human interruptibility in an office environment, but left open some questions about the robustness of such an approach. This paper examines several dimensions of robustness in sensor-based statistical models of human interruptibility. We show that real sensors can be constructed with sufficient accuracy to drive the predictive models. We also create statistical models for a much broader group of people than was studied in prior work. Finally, we examine the effects of training data quantity on the accuracy of these models and consider tradeoffs associated with different combinations of sensors. As a whole, our analyses demonstrate that sensor-based statistical models of human interruptibility can provide robust estimates for a variety of office workers in a range of circumstances, and can do so with accuracy as good as or better than people. Integrating these models into systems could support a variety of advances in human computer interaction and computer-mediated communication.
---
paper_title: Attention-Sensitive Alerting

paper_content:

We introduce utility-directed procedures for mediating the flow of potentially distracting alerts and communications to computer users. We present models and inference procedures that balance the context-sensitive costs of deferring alerts with the cost of interruption. We describe the challenge of reasoning about such costs under uncertainty via an analysis of user activity and the content of notifications. After introducing principles of attention-sensitive alerting, we focus on the problem of guiding alerts about email messages. We dwell on the problem of inferring the expected criticality of email and discuss work on the PRIORITIES system, centering on prioritizing email by criticality and modulating the communication of notifications to users about the presence and nature of incoming email.
---
paper_title: If not now, when?: the effects of interruption at different moments within task execution

paper_content:

User attention is a scarce resource, and users are susceptible to interruption overload. Systems do not reason about the effects of interrupting a user during a task sequence. In this study, we measure effects of interrupting a user at different moments within task execution in terms of task performance, emotional state, and social attribution. Task models were developed using event perception techniques, and the resulting models were used to identify interruption timings based on a user's predicted cognitive load. Our results show that different interruption moments have different impacts on user emotional state and positive social attribution, and suggest that a system could enable a user to maintain a high level of awareness while mitigating the disruptive effects of interruption. We discuss implications of these results for the design of an attention manager.
---
paper_title: Predicting human interruptibility with sensors

paper_content:

A person seeking another person's attention is normally able to quickly assess how interruptible the other person currently is. Such assessments allow behavior that we consider natural, socially appropriate, or simply polite. This is in sharp contrast to current computer and communication systems, which are largely unaware of the social situations surrounding their usage and the impact that their actions have on these situations. If systems could model human interruptibility, they could use this information to negotiate interruptions at appropriate times, thus improving human computer interaction.This article presents a series of studies that quantitatively demonstrate that simple sensors can support the construction of models that estimate human interruptibility as well as people do. These models can be constructed without using complex sensors, such as vision-based techniques, and therefore their use in everyday office environments is both practical and affordable. Although currently based on a demographically limited sample, our results indicate a substantial opportunity for future research to validate these results over larger groups of office workers. Our results also motivate the development of systems that use these models to negotiate interruptions at socially appropriate times.
---
paper_title: Examining task engagement in sensor-based statistical models of human interruptibility

paper_content:

The computer and communication systems that office workers currently use tend to interrupt at inappropriate times or unduly demand attention because they have no way to determine when an interruption is appropriate. Sensor?based statistical models of human interruptibility offer a potential solution to this problem. Prior work to examine such models has primarily reported results related to social engagement, but it seems that task engagement is also important. Using an approach developed in our prior work on sensor?based statistical models of human interruptibility, we examine task engagement by studying programmers working on a realistic programming task. After examining many potential sensors, we implement a system to log low?level input events in a development environment. We then automatically extract features from these low?level event logs and build a statistical model of interruptibility. By correctly identifying situations in which programmers are non?interruptible and minimizing cases where the model incorrectly estimates that a programmer is non?interruptible, we can support a reduction in costly interruptions while still allowing systems to convey notifications in a timely manner.
---
paper_title: Predicting human interruptibility with sensors: a Wizard of Oz feasibility study

paper_content:

A person seeking someone else's attention is normally able to quickly assess how interruptible they are. This assessment allows for behavior we perceive as natural, socially appropriate, or simply polite. On the other hand, today's computer systems are almost entirely oblivious to the human world they operate in, and typically have no way to take into account the interruptibility of the user. This paper presents a Wizard of Oz study exploring whether, and how, robust sensor-based predictions of interruptibility might be constructed, which sensors might be most useful to such predictions, and how simple such sensors might be.The study simulates a range of possible sensors through human coding of audio and video recordings. Experience sampling is used to simultaneously collect randomly distributed self-reports of interruptibility. Based on these simulated sensors, we construct statistical models predicting human interruptibility and compare their predictions with the collected self-report data. The results of these models, although covering a demographically limited sample, are very promising, with the overall accuracy of several models reaching about 78%. Additionally, a model tuned to avoiding unwanted interruptions does so for 90% of its predictions, while retaining 75% overall accuracy.
---
paper_title: Notification, Disruption, and Memory: Effects of Messaging Interruptions on Memory and Performance

paper_content:

We describe a study on the influence of instant messaging (IM) on ongoing computing tasks. The study both replicates and extends earlier work on the cost of sending notifications at different times and the sensitivity of different tasks to interruption. We investigate alternative hypotheses about the nature of disruption for a list evaluation task, an activity identified as being particularly costly to interrupt. Our findings once again show the generally disruptive effects of IM, especially during fast, stimulus-driven search tasks. In addition, we show that interruptions coming early during a search task are more likely to result in the user forgetting the primary task goal than interruptions that arrive later on. These findings have implications for the design of user interfaces and notification policies that minimize the disruptiveness of notifications.
---
paper_title: Examining the robustness of sensor-based statistical models of human interruptibility

paper_content:

Current systems often create socially awkward interruptions or unduly demand attention because they have no way of knowing if a person is busy and should not be interrupted. Previous work has examined the feasibility of using sensors and statistical models to estimate human interruptibility in an office environment, but left open some questions about the robustness of such an approach. This paper examines several dimensions of robustness in sensor-based statistical models of human interruptibility. We show that real sensors can be constructed with sufficient accuracy to drive the predictive models. We also create statistical models for a much broader group of people than was studied in prior work. Finally, we examine the effects of training data quantity on the accuracy of these models and consider tradeoffs associated with different combinations of sensors. As a whole, our analyses demonstrate that sensor-based statistical models of human interruptibility can provide robust estimates for a variety of office workers in a range of circumstances, and can do so with accuracy as good as or better than people. Integrating these models into systems could support a variety of advances in human computer interaction and computer-mediated communication.
---
paper_title: Attention-Sensitive Alerting

paper_content:

We introduce utility-directed procedures for mediating the flow of potentially distracting alerts and communications to computer users. We present models and inference procedures that balance the context-sensitive costs of deferring alerts with the cost of interruption. We describe the challenge of reasoning about such costs under uncertainty via an analysis of user activity and the content of notifications. After introducing principles of attention-sensitive alerting, we focus on the problem of guiding alerts about email messages. We dwell on the problem of inferring the expected criticality of email and discuss work on the PRIORITIES system, centering on prioritizing email by criticality and modulating the communication of notifications to users about the presence and nature of incoming email.
---
paper_title: Predicting human interruptibility with sensors

paper_content:

A person seeking another person's attention is normally able to quickly assess how interruptible the other person currently is. Such assessments allow behavior that we consider natural, socially appropriate, or simply polite. This is in sharp contrast to current computer and communication systems, which are largely unaware of the social situations surrounding their usage and the impact that their actions have on these situations. If systems could model human interruptibility, they could use this information to negotiate interruptions at appropriate times, thus improving human computer interaction.This article presents a series of studies that quantitatively demonstrate that simple sensors can support the construction of models that estimate human interruptibility as well as people do. These models can be constructed without using complex sensors, such as vision-based techniques, and therefore their use in everyday office environments is both practical and affordable. Although currently based on a demographically limited sample, our results indicate a substantial opportunity for future research to validate these results over larger groups of office workers. Our results also motivate the development of systems that use these models to negotiate interruptions at socially appropriate times.
---
paper_title: Examining task engagement in sensor-based statistical models of human interruptibility

paper_content:

The computer and communication systems that office workers currently use tend to interrupt at inappropriate times or unduly demand attention because they have no way to determine when an interruption is appropriate. Sensor?based statistical models of human interruptibility offer a potential solution to this problem. Prior work to examine such models has primarily reported results related to social engagement, but it seems that task engagement is also important. Using an approach developed in our prior work on sensor?based statistical models of human interruptibility, we examine task engagement by studying programmers working on a realistic programming task. After examining many potential sensors, we implement a system to log low?level input events in a development environment. We then automatically extract features from these low?level event logs and build a statistical model of interruptibility. By correctly identifying situations in which programmers are non?interruptible and minimizing cases where the model incorrectly estimates that a programmer is non?interruptible, we can support a reduction in costly interruptions while still allowing systems to convey notifications in a timely manner.
---
paper_title: The act of task difficulty and eye-movement frequency for the 'Oculo-motor indices'

paper_content:

The oculo-motor re ects the viewer s ability to process visual information. This paper examines whether the oculo-motor was affected by two factors: rstly task dif culty and secondly eye-movement frequency. In this paper, oculo-motor indices were de ned as measurements of pupil size, blink and eye-movement. For the purpose of this study, two experiments were designed based on previous subsequential ocular tasks were subjects were required to solve a series of mathematical problems and to orally report their calculations.The results of this experiment found that pupil size and blink rate increased in response to task dif culty in the oral calculation group. In contrast however both the saccade occurrence rate and saccade length were found to decrease with the increased dif culty of the task. The results suggests that oculo-motor indices respond to task dif culty. Secondly, eye-movement frequencies were elicited by the switching frequency of a visual target. Pupil size and the saccade time were found to increase with the frequency however, blink and gazing time were found to decrease in response to the frequency. There was a negative correlation between blinking and gazing time. Additionally, the correlation between blinking and saccade time appeared in the higher frequencies.These results indicate the oculo-motor indices are affected by both task dif culty and eye-movement frequency. Furthermore, eye-movement frequency appears to play a different role than that of task dif culty.
---
paper_title: Leveraging characteristics of task structure to predict the cost of interruption

paper_content:

A challenge in building interruption reasoning systems is to compute an accurate cost of interruption (COI). Prior work has used interface events and other cues to predict COI, but ignore characteristics related to the structure of a task. This work investigates how well characteristics of task structure can predict COI, as objectively measured by resumption lag. In an experiment, users were interrupted during task execution at various boundaries to collect a large sample of resumption lag values. Statistical methods were employed to create a parsimonious model that uses characteristics of task structure to predict COI. A subsequent experiment with different tasks showed that the model can predict COI with reasonably high accuracy. Our model can be expediently applied to many goal-directed tasks, allowing systems to make more effective decisions about when to interrupt.
---
paper_title: Pupillary dilation as a measure of attention: a quantitative system analysis

paper_content:

It has long been known that the pupil dilates as a consequence of attentional effort. But the function that relates attentional input to pupillary output has never been the subject of quantitative analysis. We present a system analysis of the pupillary response to attentional input. Attentional input is modeled as a string ofattentional pulses. We show that the system is linear; the effects of input pulses on the pupillary response are additive. The impulse response has essentially a gamma distribution with two free parameters. These parameters are estimated; they are fairly constant over tasks and subjects. The paper presents a method of estimating the string of attentional input pulses, given some average pupillary output. The method involves the technique of deconvolution; it can be implemented with a public-domain software package, Pupil.
---
paper_title: Task-Evoked Pupillary Responses, Processing Load, and the Structure of Processing Resources

paper_content:

A physiological measure of processing load or "mental effort" required to perform a cognitive task should accurately reflect within-task, between-task, and betweenindividual variations in processing demands. This article reviews all available experimental data and concludes that the task-evoked pupillary response fulfills these criteria. Alternative explanations are considered and rejected. Some implications for neurophysiological and cognitive theories of processing resources are discussed.
---
paper_title: Task-evoked pupillary response to mental workload in human-computer interaction

paper_content:

Accurate assessment of a user's mental workload will be critical for developing systems that manage user attention (interruptions) in the user interface. Empirical evidence suggests that an interruption is much less disruptive when it occurs during a period of lower mental workload. To provide a measure of mental workload for interactive tasks, we investigated the use of task-evoked pupillary response. Results show that a more difficult task demands longer processing time, induces higher subjective ratings of mental workload, and reliably evokes greater pupillary response at salient subtasks. We discuss the findings and their implications for the design of an attention manager.
---
paper_title: Notification, Disruption, and Memory: Effects of Messaging Interruptions on Memory and Performance

paper_content:

We describe a study on the influence of instant messaging (IM) on ongoing computing tasks. The study both replicates and extends earlier work on the cost of sending notifications at different times and the sensitivity of different tasks to interruption. We investigate alternative hypotheses about the nature of disruption for a list evaluation task, an activity identified as being particularly costly to interrupt. Our findings once again show the generally disruptive effects of IM, especially during fast, stimulus-driven search tasks. In addition, we show that interruptions coming early during a search task are more likely to result in the user forgetting the primary task goal than interruptions that arrive later on. These findings have implications for the design of user interfaces and notification policies that minimize the disruptiveness of notifications.
---
paper_title: Towards an index of opportunity: understanding changes in mental workload during task execution

paper_content:

To contribute to systems that reason about human attention, our work empirically demonstrates how a user's mental workload changes during task execution. We conducted a study where users performed interactive, hierarchical tasks while mental workload was measured through the use of pupil size. Results show that (i) different types of subtasks impose different mental workload, (ii) workload decreases at subtask boundaries, (iii) workload decreases more at boundaries higher in a task model and less at boundaries lower in the model, (iv) workload changes among subtask boundaries within the same level of a task model, and (v) effective understanding of why changes in workload occur requires that the measure be tightly coupled to a validated task model. From the results, we show how to map mental workload onto a computational Index of Opportunity that systems can use to better reason about human attention.
---
paper_title: Balancing Awareness and Interruption: Investigation of Notification Deferral Policies

paper_content:

We review experiments with bounded deferral, a method aimed at reducing the disruptiveness of incoming messages and alerts in return for bounded delays in receiving information. Bounded deferral provides users with a means for balancing awareness about potentially urgent information with the cost of interruption.
---
paper_title: Examining the robustness of sensor-based statistical models of human interruptibility

paper_content:

Current systems often create socially awkward interruptions or unduly demand attention because they have no way of knowing if a person is busy and should not be interrupted. Previous work has examined the feasibility of using sensors and statistical models to estimate human interruptibility in an office environment, but left open some questions about the robustness of such an approach. This paper examines several dimensions of robustness in sensor-based statistical models of human interruptibility. We show that real sensors can be constructed with sufficient accuracy to drive the predictive models. We also create statistical models for a much broader group of people than was studied in prior work. Finally, we examine the effects of training data quantity on the accuracy of these models and consider tradeoffs associated with different combinations of sensors. As a whole, our analyses demonstrate that sensor-based statistical models of human interruptibility can provide robust estimates for a variety of office workers in a range of circumstances, and can do so with accuracy as good as or better than people. Integrating these models into systems could support a variety of advances in human computer interaction and computer-mediated communication.
---
paper_title: Examining task engagement in sensor-based statistical models of human interruptibility

paper_content:

The computer and communication systems that office workers currently use tend to interrupt at inappropriate times or unduly demand attention because they have no way to determine when an interruption is appropriate. Sensor?based statistical models of human interruptibility offer a potential solution to this problem. Prior work to examine such models has primarily reported results related to social engagement, but it seems that task engagement is also important. Using an approach developed in our prior work on sensor?based statistical models of human interruptibility, we examine task engagement by studying programmers working on a realistic programming task. After examining many potential sensors, we implement a system to log low?level input events in a development environment. We then automatically extract features from these low?level event logs and build a statistical model of interruptibility. By correctly identifying situations in which programmers are non?interruptible and minimizing cases where the model incorrectly estimates that a programmer is non?interruptible, we can support a reduction in costly interruptions while still allowing systems to convey notifications in a timely manner.
---
paper_title: The act of task difficulty and eye-movement frequency for the 'Oculo-motor indices'

paper_content:

The oculo-motor re ects the viewer s ability to process visual information. This paper examines whether the oculo-motor was affected by two factors: rstly task dif culty and secondly eye-movement frequency. In this paper, oculo-motor indices were de ned as measurements of pupil size, blink and eye-movement. For the purpose of this study, two experiments were designed based on previous subsequential ocular tasks were subjects were required to solve a series of mathematical problems and to orally report their calculations.The results of this experiment found that pupil size and blink rate increased in response to task dif culty in the oral calculation group. In contrast however both the saccade occurrence rate and saccade length were found to decrease with the increased dif culty of the task. The results suggests that oculo-motor indices respond to task dif culty. Secondly, eye-movement frequencies were elicited by the switching frequency of a visual target. Pupil size and the saccade time were found to increase with the frequency however, blink and gazing time were found to decrease in response to the frequency. There was a negative correlation between blinking and gazing time. Additionally, the correlation between blinking and saccade time appeared in the higher frequencies.These results indicate the oculo-motor indices are affected by both task dif culty and eye-movement frequency. Furthermore, eye-movement frequency appears to play a different role than that of task dif culty.
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paper_title: Lilsys: Sensing Unavailability

paper_content:

As communications systems increasingly gather and propagate information about people's reachability or ``presence'', users need better tools to minimize undesired interruptions while allowing desired ones. We review the salient elements of presence and availability that people use when initiating face-to-face communication. We discuss problems with current strategies for managing one's availability in telecommunication media. We describe a prototype system called Lilsys which passively collects availability cues gathered from users' actions and environment using ambient sensors and provides machine inferencing of unavailability. We discuss observations and design implications from deploying Lilsys.
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paper_title: Leveraging characteristics of task structure to predict the cost of interruption

paper_content:

A challenge in building interruption reasoning systems is to compute an accurate cost of interruption (COI). Prior work has used interface events and other cues to predict COI, but ignore characteristics related to the structure of a task. This work investigates how well characteristics of task structure can predict COI, as objectively measured by resumption lag. In an experiment, users were interrupted during task execution at various boundaries to collect a large sample of resumption lag values. Statistical methods were employed to create a parsimonious model that uses characteristics of task structure to predict COI. A subsequent experiment with different tasks showed that the model can predict COI with reasonably high accuracy. Our model can be expediently applied to many goal-directed tasks, allowing systems to make more effective decisions about when to interrupt.
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paper_title: Pupillary dilation as a measure of attention: a quantitative system analysis

paper_content:

It has long been known that the pupil dilates as a consequence of attentional effort. But the function that relates attentional input to pupillary output has never been the subject of quantitative analysis. We present a system analysis of the pupillary response to attentional input. Attentional input is modeled as a string ofattentional pulses. We show that the system is linear; the effects of input pulses on the pupillary response are additive. The impulse response has essentially a gamma distribution with two free parameters. These parameters are estimated; they are fairly constant over tasks and subjects. The paper presents a method of estimating the string of attentional input pulses, given some average pupillary output. The method involves the technique of deconvolution; it can be implemented with a public-domain software package, Pupil.
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paper_title: Task-Evoked Pupillary Responses, Processing Load, and the Structure of Processing Resources

paper_content:

A physiological measure of processing load or "mental effort" required to perform a cognitive task should accurately reflect within-task, between-task, and betweenindividual variations in processing demands. This article reviews all available experimental data and concludes that the task-evoked pupillary response fulfills these criteria. Alternative explanations are considered and rejected. Some implications for neurophysiological and cognitive theories of processing resources are discussed.
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paper_title: Task-evoked pupillary response to mental workload in human-computer interaction

paper_content:

Accurate assessment of a user's mental workload will be critical for developing systems that manage user attention (interruptions) in the user interface. Empirical evidence suggests that an interruption is much less disruptive when it occurs during a period of lower mental workload. To provide a measure of mental workload for interactive tasks, we investigated the use of task-evoked pupillary response. Results show that a more difficult task demands longer processing time, induces higher subjective ratings of mental workload, and reliably evokes greater pupillary response at salient subtasks. We discuss the findings and their implications for the design of an attention manager.
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paper_title: BusyBody: creating and fielding personalized models of the cost of interruption

paper_content:

Interest has been growing in opportunities to build and deploy statistical models that can infer a computer user's current interruptability from computer activity and relevant contextual information. We describe a system that intermittently asks users to assess their perceived interruptability during a training phase and that builds decision-theoretic models with the ability to predict the cost of interrupting the user. The models are used at run-time to compute the expected cost of interruptions, providing a mediator for incoming notifications, based on a consideration of a user's current and recent history of computer activity, meeting status, location, time of day, and whether a conversation is detected.
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paper_title: Towards an index of opportunity: understanding changes in mental workload during task execution

paper_content:

To contribute to systems that reason about human attention, our work empirically demonstrates how a user's mental workload changes during task execution. We conducted a study where users performed interactive, hierarchical tasks while mental workload was measured through the use of pupil size. Results show that (i) different types of subtasks impose different mental workload, (ii) workload decreases at subtask boundaries, (iii) workload decreases more at boundaries higher in a task model and less at boundaries lower in the model, (iv) workload changes among subtask boundaries within the same level of a task model, and (v) effective understanding of why changes in workload occur requires that the measure be tightly coupled to a validated task model. From the results, we show how to map mental workload onto a computational Index of Opportunity that systems can use to better reason about human attention.
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paper_title: Balancing Awareness and Interruption: Investigation of Notification Deferral Policies

paper_content:

We review experiments with bounded deferral, a method aimed at reducing the disruptiveness of incoming messages and alerts in return for bounded delays in receiving information. Bounded deferral provides users with a means for balancing awareness about potentially urgent information with the cost of interruption.
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paper_title: Examining the robustness of sensor-based statistical models of human interruptibility

paper_content:

Current systems often create socially awkward interruptions or unduly demand attention because they have no way of knowing if a person is busy and should not be interrupted. Previous work has examined the feasibility of using sensors and statistical models to estimate human interruptibility in an office environment, but left open some questions about the robustness of such an approach. This paper examines several dimensions of robustness in sensor-based statistical models of human interruptibility. We show that real sensors can be constructed with sufficient accuracy to drive the predictive models. We also create statistical models for a much broader group of people than was studied in prior work. Finally, we examine the effects of training data quantity on the accuracy of these models and consider tradeoffs associated with different combinations of sensors. As a whole, our analyses demonstrate that sensor-based statistical models of human interruptibility can provide robust estimates for a variety of office workers in a range of circumstances, and can do so with accuracy as good as or better than people. Integrating these models into systems could support a variety of advances in human computer interaction and computer-mediated communication.
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paper_title: If not now, when?: the effects of interruption at different moments within task execution

paper_content:

User attention is a scarce resource, and users are susceptible to interruption overload. Systems do not reason about the effects of interrupting a user during a task sequence. In this study, we measure effects of interrupting a user at different moments within task execution in terms of task performance, emotional state, and social attribution. Task models were developed using event perception techniques, and the resulting models were used to identify interruption timings based on a user's predicted cognitive load. Our results show that different interruption moments have different impacts on user emotional state and positive social attribution, and suggest that a system could enable a user to maintain a high level of awareness while mitigating the disruptive effects of interruption. We discuss implications of these results for the design of an attention manager.
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paper_title: Understanding and developing models for detecting and differentiating breakpoints during interactive tasks

paper_content:

The ability to detect and differentiate breakpoints during task execution is critical for enabling defer-to-breakpoint policies within interruption management. In this work, we examine the feasibility of building statistical models that can detect and differentiate three granularities (types) of perceptually meaningful breakpoints during task execution, without having to recognize the underlying tasks. We collected ecological samples of task execution data, and asked observers to review the interaction in the collected videos and identify any perceived breakpoints and their type. Statistical methods were applied to learn models that map features of the interaction to each type of breakpoint. Results showed that the models were able to detect and differentiate breakpoints with reasonably high accuracy across tasks. Among many uses, our resulting models can enable interruption management systems to better realize defer-to-breakpoint policies for interactive, free-form tasks.
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paper_title: A method, system, and tools for intelligent interruption management

paper_content:

Interrupting users engaged in tasks typically has negative effects on their task completion time, error rate, and affective state. Empirical research has shown that these negative effects can be mitigated by deferring interruptions until more opportune moments in a user's task sequence. However, existing systems that reason about when to interrupt do not have access to task models that would allow for such finer-grained temporal reasoning. We outline our method of finding opportune moments that links a physiological measure of workload with task modeling techniques and theories of attention. We describe the design and implementation of our interruption management system, showing how it can be used to specify and monitor practical, representative user tasks. We discuss our ongoing empirical work in this area, and how the use of our framework may enable attention aware systems to consider a user's position in a task when reasoning about when to interrupt.
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paper_title: Examining task engagement in sensor-based statistical models of human interruptibility

paper_content:

The computer and communication systems that office workers currently use tend to interrupt at inappropriate times or unduly demand attention because they have no way to determine when an interruption is appropriate. Sensor?based statistical models of human interruptibility offer a potential solution to this problem. Prior work to examine such models has primarily reported results related to social engagement, but it seems that task engagement is also important. Using an approach developed in our prior work on sensor?based statistical models of human interruptibility, we examine task engagement by studying programmers working on a realistic programming task. After examining many potential sensors, we implement a system to log low?level input events in a development environment. We then automatically extract features from these low?level event logs and build a statistical model of interruptibility. By correctly identifying situations in which programmers are non?interruptible and minimizing cases where the model incorrectly estimates that a programmer is non?interruptible, we can support a reduction in costly interruptions while still allowing systems to convey notifications in a timely manner.
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paper_title: I've got 99 problems, but vibration ain't one: a survey of smartphone users' concerns

paper_content:

Smartphone operating systems warn users when third-party applications try to access sensitive functions or data. However, all of the major smartphone platforms warn users about different application actions. To our knowledge, their selection of warnings was not grounded in user research; past research on mobile privacy has focused exclusively on the risks pertained to sharing location. To expand the scope of smartphone security and privacy research, we surveyed 3,115 smartphone users about 99 risks associated with 54 smartphone privileges. We asked participants to rate how upset they would be if given risks occurred and used this data to rank risks by levels of user concern. We then asked 41 smartphone users to discuss the risks in their own words; their responses confirmed that people find the lowest-ranked risks merely annoying but might seek legal or financial retribution for the highest-ranked risks. In order to determine the relative frequency of risks, we also surveyed the 3,115 users about experiences with "misbehaving" applications. Our ranking and frequency data can be used to guide the selection of warnings on smartphone platforms.
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paper_title: Understanding the Role of Places and Activities on Mobile Phone Interaction and Usage Patterns

paper_content:

User interaction patterns with mobile apps and notifications are generally complex due to the many factors involved. However a deep understanding of what influences them can lead to more acceptable applications that are able to deliver information at the right time. In this paper, we present for the first time an in-depth analysis of interaction behavior with notifications in relation to the location and activity of users. We conducted an in-situ study for a period of two weeks to collect more than 36,000 notifications, 17,000 instances of application usage, 77,000 location samples, and 487 days of daily activity entries from 26 students at a UK university. Our results show that users’ attention towards new notifications and willingness to accept them are strongly linked to the location they are in and in minor part to their current activity. We consider both users’ receptivity and attentiveness, and we show that different response behaviors are associated to different locations. These findings are fundamental from a design perspective since they allow us to understand how certain types of places are linked to specific types of interaction behavior. This information can be used as a basis for the development of novel intelligent mobile applications and services.
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paper_title: An in-situ study of mobile phone notifications

paper_content:

Notifications on mobile phones alert users about new messages, emails, social network updates, and other events. However, little is understood about the nature and effect of such notifications on the daily lives of mobile users. We report from a one-week, in-situ study involving 15 mobile phones users, where we collected real-world notifications through a smartphone logging application alongside subjective perceptions of those notifications through an online diary. We found that our participants had to deal with 63.5 notifications on average per day, mostly from messengers and email. Whether the phone is in silent mode or not, notifications were typically viewed within minutes. Social pressure in personal communication was amongst the main reasons given. While an increasing number of notifications was associated with an increase in negative emotions, receiving more messages and social network updates also made our participants feel more connected with others. Our findings imply that avoiding interruptions from notifications may be viable for professional communication, while in personal communication, approaches should focus on managing expectations.
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paper_title: Designing content-driven intelligent notification mechanisms for mobile applications

paper_content:

An increasing number of notifications demanding the smartphone user's attention, often arrive at an inappropriate moment, or carry irrelevant content. In this paper we present a study of mobile user interruptibility with respect to notification content, its sender, and the context in which a notification is received. In a real-world study we collect around 70,000 instances of notifications from 35 users. We group notifications according to the applications that initiated them, and the social relationship between the sender and the receiver. Then, by considering both content and context information, such as the current activity of a user, we discuss the design of classifiers for learning the most opportune moment for the delivery of a notification carrying a specific type of information. Our results show that such classifiers lead to a more accurate prediction of users' interruptibility than an alternative approach based on user-defined rules of their own interruptibility.
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paper_title: Notifications and awareness: a field study of alert usage and preferences

paper_content:

Desktop notifications are designed to provide awareness of information while a user is attending to a primary task. Unfortunately the awareness can come with the price of disruption to the focal task. We review results of a field study on the use and perceived value of email notifications in the workplace. We recorded users' interactions with software applications for two weeks and studied how notifications or their forced absence influenced users' quest for awareness of new email arrival, as well as the impact of notifications on their overall task focus. Results showed that users view notifications as a mechanism to provide passive awareness rather than a trigger to switch tasks. Turing off notifications cause some users to self interrupt more to explicitly monitor email arrival, while others appear to be able to better focus on their tasks. Users acknowledge notifications as disruptive, yet opt for them because of their perceived value in providing awareness.
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paper_title: My Phone and Me: Understanding People's Receptivity to Mobile Notifications

paper_content:

Notifications are extremely beneficial to users, but they often demand their attention at inappropriate moments. In this paper we present an in-situ study of mobile interruptibility focusing on the effect of cognitive and physical factors on the response time and the disruption perceived from a notification. Through a mixed method of automated smartphone logging and experience sampling we collected 10372 in-the-wild notifications and 474 questionnaire responses on notification perception from 20 users. We found that the response time and the perceived disruption from a notification can be influenced by its presentation, alert type, sender-recipient relationship as well as the type, completion level and complexity of the task in which the user is engaged. We found that even a notification that contains important or useful content can cause disruption. Finally, we observe the substantial role of the psychological traits of the individuals on the response time and the disruption perceived from a notification.
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paper_title: Large-scale assessment of mobile notifications

paper_content:

Notifications are a core feature of mobile phones. They inform users about a variety of events. Users may take immediate action or ignore them depending on the importance of a notification as well as their current context. The nature of notifications is manifold, applications use them both sparsely and frequently. In this paper we present the first large-scale analysis of mobile notifications with a focus on users' subjective perceptions. We derive a holistic picture of notifications on mobile phones by collecting close to 200 million notifications from more than 40,000 users. Using a data-driven approach, we break down what users like and dislike about notifications. Our results reveal differences in importance of notifications and how users value notifications from messaging apps as well as notifications that include information about people and events. Based on these results we derive a number of findings about the nature of notifications and guidelines to effectively use them.
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paper_title: Managing Smartphone Interruptions through Adaptive Modes and Modulation of Notifications

paper_content:

Smartphones are capable of alerting their users to different kinds of digital interruption using different modalities and with varying modulation. Smart notification is the capability of a smartphone for selecting the user's preferred kind of alert in particular situations using the full vocabulary of notification modalities and modulations. It therefore goes well beyond attempts to predict if or when to silence a ringing phone call. We demonstrate smart notification for messages received from a document retrieval system while the user is attending a meeting. The notification manager learns about their notification preferences from users' judgements about videos of meetings. It takes account of the relevance of the interruption to the meeting, whether the user is busy and the sensed location of the smartphone. Through repeated training, the notification manager learns to reliably predict the preferred notification modes for users and this learning continues to improve with use.
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paper_title: Investigating Mobile Users' Ringer Mode Usage and Attentiveness and Responsiveness to Communication

paper_content:

Smartphones are considered to be "always on, always connected" but mobile users are not always attentive and responsive to incoming communication. We present a mixed methods study investigating how mobile users use ringer modes for managing interruption by and awareness of incoming communication, and how these practices and locales affect their attentiveness and responsiveness. We show that mobile users have diverse ringer mode usage, but they switch ringer modes mainly for three purposes: avoiding interruption, preventing the phone from disrupting the environment, and noticing important notifications. In addition, without signals of notifications, users are less likely to immediately attend to notifications, but they are not less responsive to those they have attended. Finally, ringer mode switches, attentiveness, and responsiveness are all correlated with certain locales. We discuss implications from these findings, and suggest how future CMC tools and notification services take different purposes for using ringer modes and locales into consideration.
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paper_title: MyTraces: Investigating Correlation and Causation between Users’ Emotional States and Mobile Phone Interaction

paper_content:

Most of the existing work concerning the analysis of emotional states and mobile phone interaction has been based on correlation analysis. In this paper, for the first time, we carry out a causality study to investigate the causal links between users’ emotional states and their interaction with mobile phones, which could provide valuable information to practitioners and researchers. The analysis is based on a dataset collected in-the-wild. We recorded 5,118 mood reports from 28 users over a period of 20 days. Our results show that users’ emotions have a causal impact on different aspects of mobile phone interaction. On the other hand, we can observe a causal impact of the use of specific applications, reflecting the external users’ context, such as socializing and traveling, on happiness and stress level. This study has profound implications for the design of interactive mobile systems since it identifies the dimensions that have causal effects on users’ interaction with mobile phones and vice versa. These findings might lead to the design of more effective computing systems and services that rely on the analysis of the emotional state of users, for example for marketing and digital health applications.
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paper_title: Assessing the Relationship between Technical Affinity, Stress and Notifications on Smartphones

paper_content:

Smartphones have become an indispensable part of everyday life. By this time, push notifications are at the core of many apps, proactively pushing new content to users. These notifications may raise awareness, but also have the downside of being disruptive. In this paper we present a laboratory study investigating users' attitudes towards notifications and how they deal with notification settings on their smartphones. Permission requests for sending push notifications on iOS don't inform the user about the nature of notifications of this app, leaving the user to make a rather uninformed choice on whether to accept or deny. We show that requests including explanations are significantly more likely to be accepted. Our results further indicate that apart from being disruptive, notifications may create stress due to information overload. Notification settings, once assigned a preset, are rarely changed, although not necessarily matching the favored one.
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paper_title: Bayesphone: Precomputation of context-sensitive policies for inquiry and action in mobile devices

paper_content:

Inference and decision making with probabilistic user models may be infeasible on portable devices such as cell phones. We highlight the opportunity for storing and using precomputed inferences about ideal actions for future situations, based on offline learning and reasoning with the user models. As a motivating example, we focus on the use precomputation of call-handling policies for cell phones. The methods hinge on the learning of Bayesian user models for predicting whether users will attend meetings on their calendar and the cost of being interrupted by incoming calls should a meeting be attended.
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paper_title: Using Decision-Theoretic Experience Sampling to Build Personalized Mobile Phone Interruption Models

paper_content:

We contribute a method for approximating users' interruptibility costs to use for experience sampling and validate the method in an application that learns when to automatically turn off and on the phone volume to avoid embarrassing phone interruptions. We demonstrate that users have varying costs associated with interruptions which indicates the need for personalized cost approximations. We compare different experience sampling techniques to learn users' volume preferences and show those that ask when our cost approximation is low reduce the number of embarrassing interruptions and result in more accurate volume classifiers when deployed for long-term use.
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paper_title: Using context-aware computing to reduce the perceived burden of interruptions from mobile devices

paper_content:

The potential for sensor-enabled mobile devices to proactively present information when and where users need it ranks among the greatest promises of ubiquitous computing. Unfortunately, mobile phones, PDAs, and other computing devices that compete for the user's attention can contribute to interruption irritability and feelings of information overload. Designers of mobile computing interfaces, therefore, require strategies for minimizing the perceived interruption burden of proactively delivered messages. In this work, a context-aware mobile computing device was developed that automatically detects postural and ambulatory activity transitions in real time using wireless accelerometers. This device was used to experimentally measure the receptivity to interruptions delivered at activity transitions relative to those delivered at random times. Messages delivered at activity transitions were found to be better received, thereby suggesting a viable strategy for context-aware message delivery in sensor-enabled mobile computing devices.
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paper_title: Towards attention-aware adaptive notification on smart phones

paper_content:

As the amount of information to users increases with the trends of an increasing numbers of devices, applications, and web services, the new bottleneck in computing is human attention. To minimize users attentional overload, we propose a novel middleware "Attelia" that detects breakpoints of user's mobile interactions to deliver notifications adaptively. Attelia detects such timings in real-time, using only users phones, without any external sensors, and without any modifications to applications. Our extensive evaluation proved Attelias effectiveness. In-the-wild user study with 30 participants for 16 days showed that, specifically for the users with greater sensitivity for interruptive notification timings, notification scheduling in Attelia's breakpoint timing reduced users frustration by 28% in users' real smart phone environments.
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paper_title: Investigating episodes of mobile phone activity as indicators of opportune moments to deliver notifications

paper_content:

We investigate whether opportune moments to deliver notifications surface at the endings of episodes of mobile interaction (making voice calls or receiving SMS) based on the assumption that the endings collocate with naturally occurring breakpoint in the user's primary task. Testing this with a naturalistic experiment we find that interruptions (notifications) are attended to and dealt with significantly more quickly after a user has finished an episode of mobile interaction compared to a random baseline condition, supporting the potential utility of this notification strategy. We also find that the workload and situational appropriateness of the secondary interruption task significantly affect subsequent delay and completion rate of the tasks. In situ self-reports and interviews reveal complexities in the subjective experience of the interruption, which suggest that a more nuanced classification of the particular call or SMS and its relationship to the primary task(s) would be desirable.
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paper_title: Development of NASA-TLX (Task Load Index): Results of Empirical and Theoretical Research

paper_content:

Abstract The results of a multi-year research program to identify the factors associated with variations in subjective workload within and between different types of tasks are reviewed. Subjective evaluations of 10 workload-related factors were obtained from 16 different experiments. The experimental tasks included simple cognitive and manual control tasks, complex laboratory and supervisory control tasks, and aircraft simulation. Task-, behavior-, and subject-related correlates of subjective workload experiences varied as a function of difficulty manipulations within experiments, different sources of workload between experiments, and individual differences in workload definition. A multi-dimensional rating scale is proposed in which information about the magnitude and sources of six workload-related factors are combined to derive a sensitive and reliable estimate of workload.
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paper_title: Towards unobtrusive emotion recognition for affective social communication

paper_content:

Awareness of the emotion of those who communicate with others is a fundamental challenge in building affective intelligent systems. Emotion is a complex state of the mind influenced by external events, physiological changes, or relationships with others. Because emotions can represent a user's internal context or intention, researchers suggested various methods to measure the user's emotions from analysis of physiological signals, facial expressions, or voice. However, existing methods have practical limitations to be used with consumer devices, such as smartphones; they may cause inconvenience to users and require special equipment such as a skin conductance sensor. Our approach is to recognize emotions of the user by inconspicuously collecting and analyzing user-generated data from different types of sensors on the smartphone. To achieve this, we adopted a machine learning approach to gather, analyze and classify device usage patterns, and developed a social network service client for Android smartphones which unobtrusively find various behavioral patterns and the current context of users. Also, we conducted a pilot study to gather real-world data which imply various behaviors and situations of a participant in her/his everyday life. From these data, we extracted 10 features and applied them to build a Bayesian Network classifier for emotion recognition. Experimental results show that our system can classify user emotions into 7 classes such as happiness, surprise, anger, disgust, sadness, fear, and neutral with a surprisingly high accuracy. The proposed system applied to a smartphone demonstrated the feasibility of an unobtrusive emotion recognition approach and a user scenario for emotion-oriented social communication between users.
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paper_title: InterruptMe: designing intelligent prompting mechanisms for pervasive applications

paper_content:

The mobile phone represents a unique platform for interactive applications that can harness the opportunity of an immediate contact with a user in order to increase the impact of the delivered information. However, this accessibility does not necessarily translate to reachability, as recipients might refuse an initiated contact or disfavor a message that comes in an inappropriate moment. In this paper we seek to answer whether, and how, suitable moments for interruption can be identified and utilized in a mobile system. We gather and analyze a real-world smartphone data trace and show that users' broader context, including their activity, location, time of day, emotions and engagement, determine different aspects of interruptibility. We then design and implement InterruptMe, an interruption management library for Android smartphones. An extensive experiment shows that, compared to a context-unaware approach, interruptions elicited through our library result in increased user satisfaction and shorter response times.
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paper_title: Didn't you see my message?: predicting attentiveness to mobile instant messages

paper_content:

Mobile instant messaging (e.g., via SMS or WhatsApp) often goes along with an expectation of high attentiveness, i.e., that the receiver will notice and read the message within a few minutes. Hence, existing instant messaging services for mobile phones share indicators of availability, such as the last time the user has been online. However, in this paper we not only provide evidence that these cues create social pressure, but that they are also weak predictors of attentiveness. As remedy, we propose to share a machine-computed prediction of whether the user will view a message within the next few minutes or not. For two weeks, we collected behavioral data from 24 users of mobile instant messaging services. By the means of machine-learning techniques, we identified that simple features extracted from the phone, such as the user's interaction with the notification center, the screen activity, the proximity sensor, and the ringer mode, are strong predictors of how quickly the user will attend to the messages. With seven automatically selected features our model predicts whether a phone user will view a message within a few minutes with 70.6% accuracy and a precision for fast attendance of 81.2%
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paper_title: Designing content-driven intelligent notification mechanisms for mobile applications

paper_content:

An increasing number of notifications demanding the smartphone user's attention, often arrive at an inappropriate moment, or carry irrelevant content. In this paper we present a study of mobile user interruptibility with respect to notification content, its sender, and the context in which a notification is received. In a real-world study we collect around 70,000 instances of notifications from 35 users. We group notifications according to the applications that initiated them, and the social relationship between the sender and the receiver. Then, by considering both content and context information, such as the current activity of a user, we discuss the design of classifiers for learning the most opportune moment for the delivery of a notification carrying a specific type of information. Our results show that such classifiers lead to a more accurate prediction of users' interruptibility than an alternative approach based on user-defined rules of their own interruptibility.
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paper_title: A survey of mobile phone sensing

paper_content:

Mobile phones or smartphones are rapidly becoming the central computer and communication device in people's lives. Application delivery channels such as the Apple AppStore are transforming mobile phones into App Phones, capable of downloading a myriad of applications in an instant. Importantly, today's smartphones are programmable and come with a growing set of cheap powerful embedded sensors, such as an accelerometer, digital compass, gyroscope, GPS, microphone, and camera, which are enabling the emergence of personal, group, and communityscale sensing applications. We believe that sensor-equipped mobile phones will revolutionize many sectors of our economy, including business, healthcare, social networks, environmental monitoring, and transportation. In this article we survey existing mobile phone sensing algorithms, applications, and systems. We discuss the emerging sensing paradigms, and formulate an architectural framework for discussing a number of the open issues and challenges emerging in the new area of mobile phone sensing research.
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paper_title: Towards multi-modal anticipatory monitoring of depressive states through the analysis of human-smartphone interaction

paper_content:

Remarkable advances in smartphone technology, especially in terms of passive sensing, have enabled researchers to passively monitor user behavior in real-time and at a granularity that was not possible just a few years ago. Recently, different approaches have been proposed to investigate the use of different sensing and phone interaction features, including location, call, SMS and overall application usage logs, to infer the depressive state of users. In this paper, we propose an approach for monitoring of depressive states using multi-modal sensing via smartphones. Through a brief literature review we show the sensing modalities that have been exploited in the past studies for monitoring depression. We then present the initial results of an ongoing study to demonstrate the association of depressive states with the smartphone interaction features. Finally, we discuss the challenges in predicting depression through multimodal mobile sensing.
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paper_title: EmotionSense: a mobile phones based adaptive platform for experimental social psychology research

paper_content:

Today's mobile phones represent a rich and powerful computing platform, given their sensing, processing and communication capabilities. Phones are also part of the everyday life of billions of people, and therefore represent an exceptionally suitable tool for conducting social and psychological experiments in an unobtrusive way. de the ability of sensing individual emotions as well as activities, verbal and proximity interactions among members of social groups. Moreover, the system is programmable by means of a declarative language that can be used to express adaptive rules to improve power saving. We evaluate a system prototype on Nokia Symbian phones by means of several small-scale experiments aimed at testing performance in terms of accuracy and power consumption. Finally, we present the results of real deployment where we study participants emotions and interactions. We cross-validate our measurements with the results obtained through questionnaires filled by the users, and the results presented in social psychological studies using traditional methods. In particular, we show how speakers and participants' emotions can be automatically detected by means of classifiers running locally on off-the-shelf mobile phones, and how speaking and interactions can be correlated with activity and location measures.
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paper_title: Enabling large-scale human activity inference on smartphones using community similarity networks (csn)

paper_content:

Sensor-enabled smartphones are opening a new frontier in the development of mobile sensing applications. The recognition of human activities and context from sensor-data using classification models underpins these emerging applications. However, conventional approaches to training classifiers struggle to cope with the diverse user populations routinely found in large-scale popular mobile applications. Differences between users (e.g., age, sex, behavioral patterns, lifestyle) confuse classifiers, which assume everyone is the same. To address this, we propose Community Similarity Networks (CSN), which incorporates inter-person similarity measurements into the classifier training process. Under CSN every user has a unique classifier that is tuned to their own characteristics. CSN exploits crowd-sourced sensor-data to personalize classifiers with data contributed from other similar users. This process is guided by similarity networks that measure different dimensions of inter-person similarity. Our experiments show CSN outperforms existing approaches to classifier training under the presence of population diversity.
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paper_title: SenSocial: a middleware for integrating online social networks and mobile sensing data streams

paper_content:

Smartphone sensing enables inference of physical context, while online social networks (OSNs) allow mobile applications to harness users' interpersonal relationships. However, OSNs and smartphone sensing remain disconnected, since obstacles, including the synchronization of mobile sensing and OSN monitoring, inefficiency of smartphone sensors, and privacy concerns, stand in the way of merging the information from these two sources. ::: In this paper we present the design, implementation and evaluation of SenSocial, a middleware that automates the process of obtaining and joining OSN and physical context data streams for the development of ubiquitous computing applications. SenSocial enables instantiation, management and aggregation of context streams from multiple remote devices. Through micro-benchmarks we show that SenSocial successfully and efficiently captures OSN and mobile sensed data streams. We developed two prototype applications in order to evaluate our middleware and we demonstrate that SenSocial significantly reduces the amount of programming effort needed for building social sensing applications.
---
paper_title: I'll be there for you: Quantifying Attentiveness towards Mobile Messaging

paper_content:

Social norm has it that people are expected to respond to mobile phone messages quickly. We investigate how attentive people really are and how timely they actually check and triage new messages throughout the day. By collecting more than 55,000 messages from 42 mobile phone users over the course of two weeks, we were able to predict people's attentiveness through their mobile phone usage with close to 80% accuracy. We found that people were attentive to messages 12.1 hours a day, i.e. 84.8 hours per week, and provide statistical evidence how very short people's inattentiveness lasts: in 75% of the cases mobile phone users return to their attentive state within 5 minutes. In this paper, we present a comprehensive analysis of attentiveness throughout each hour of the day and show that intelligent notification delivery services, such as bounded deferral, can assume that inattentiveness will be rare and subside quickly.
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paper_title: Large-scale evaluation of call-availability prediction

paper_content:

We contribute evidence to which extent sensor- and contextual information available on mobile phones allow to predict whether a user would pick up a call or not. Using an app publicly available for Android phones, we logged anonymous data from 31311 calls of 418 different users. The data shows that information easily available in mobile phones, such as the time since the last call, the time since the last ringer mode change, or the device posture, can predict call availability with an accuracy of 83.2% (Kappa = .646). Personalized models can increase the accuracy to 87% on average. Features related to when the user was last active turned out to be strong predictors. This shows that simple contextual cues approximating user activity are worthwhile investigating when designing context-aware ubiquitous communication systems.
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paper_title: Trajectories of depression: unobtrusive monitoring of depressive states by means of smartphone mobility traces analysis

paper_content:

One of the most interesting applications of mobile sensing is monitoring of individual behavior, especially in the area of mental health care. Most existing systems require an interaction with the device, for example they may require the user to input his/her mood state at regular intervals. In this paper we seek to answer whether mobile phones can be used to unobtrusively monitor individuals affected by depressive mood disorders by analyzing only their mobility patterns from GPS traces. In order to get ground-truth measurements, we have developed a smartphone application that periodically collects the locations of the users and the answers to daily questionnaires that quantify their depressive mood. We demonstrate that there exists a significant correlation between mobility trace characteristics and the depressive moods. Finally, we present the design of models that are able to successfully predict changes in the depressive mood of individuals by analyzing their movements.
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paper_title: StressSense: detecting stress in unconstrained acoustic environments using smartphones

paper_content:

Stress can have long term adverse effects on individuals' physical and mental well-being. Changes in the speech production process is one of many physiological changes that happen during stress. Microphones, embedded in mobile phones and carried ubiquitously by people, provide the opportunity to continuously and non-invasively monitor stress in real-life situations. We propose StressSense for unobtrusively recognizing stress from human voice using smartphones. We investigate methods for adapting a one-size-fits-all stress model to individual speakers and scenarios. We demonstrate that the StressSense classifier can robustly identify stress across multiple individuals in diverse acoustic environments: using model adaptation StressSense achieves 81% and 76% accuracy for indoor and outdoor environments, respectively. We show that StressSense can be implemented on commodity Android phones and run in real-time. To the best of our knowledge, StressSense represents the first system to consider voice based stress detection and model adaptation in diverse real-life conversational situations using smartphones.
---
paper_title: Bewell: A smartphone application to monitor, model and promote wellbeing

paper_content:

A key challenge for mobile health is to develop new technology that can assist individuals in maintaining a healthy lifestyle by keeping track of their everyday behaviors. Smartphones embedded with a wide variety of sensors are enabling a new generation of personal health applications that can actively monitor, model and promote wellbeing. Automated wellbeing tracking systems available so far have focused on physical fitness and sleep and often require external non-phone based sensors. In this work, we take a step towards a more comprehensive smartphone based system that can track activities that impact physical, social, and mental wellbeing namely, sleep, physical activity, and social interactions and provides intelligent feedback to promote better health. We present the design, implementation and evaluation of BeWell, an automated wellbeing app for the Android smartphones and demonstrate its feasibility in monitoring multi-dimensional wellbeing. By providing a more complete picture of health, BeWell has the potential to empower individuals to improve their overall wellbeing and identify any early signs of decline.
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paper_title: Conceptualizing Interpersonal Interruption Management: A Theoretical Framework and Research Program

paper_content:

Previous research exploring interpersonal-technology-mediated interruptions has focused on understanding how the knowledge of an individual's local context can be utilized to reduce unwanted intrusions by employing sensor and agent technology to detect and manage their interruptions. However, this approach has produced limited benefit for users because it fails to take into account who the interruption is from or what it is about. To address this deficiency a theoretical framework and associated research program is presented to provide a fresh perspective on design of interruption management tools.
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paper_title: Effects of Content and Time of Delivery on Receptivity to Mobile Interruptions

paper_content:

In this paper we investigate effects of the content of interruptions and of the time of interruption delivery on mobile phones. We review related work and report on a naturalistic quasi-experiment using experience-sampling that showed that the receptivity to an interruption is influenced by its content rather than by its time of delivery in the employed modality of delivery - SMS. We also examined the underlying variables that increase the perceived quality of content and found that the factors interest, entertainment, relevance and actionability influence people's receptivity significantly. Our findings inform system design that seeks to provide context-sensitive information or to predict interruptibility and suggest the consideration of receptivity as an extension to the way we think and reason about interruptibility.
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paper_title: Oasis: A framework for linking notification delivery to the perceptual structure of goal-directed tasks

paper_content:

A notification represents the proactive delivery of information to a user and reduces the need to visually scan or repeatedly check an external information source. At the same time, notifications often interrupt user tasks at inopportune moments, decreasing productivity and increasing frustration. Controlled studies have shown that linking notification delivery to the perceptual structure of a user's tasks can reduce these interruption costs. However, in these studies, the scheduling was always performed manually, and it was not clear whether it would be possible for a system to mimic similar techniques. This article contributes the design and implementation of a novel system called Oasis that aligns notification scheduling with the perceptual structure of user tasks. We describe the architecture of the system, how it detects task structure on the fly without explicit knowledge of the task itself, and how it layers flexible notification scheduling policies on top of this detection mechanism. The system also includes an offline tool for creating customized statistical models for detecting task structure. The value of our system is that it intelligently schedules notifications, enabling the reductions in interruption costs shown within prior controlled studies to now be realized by users in everyday desktop computing tasks. It also provides a test bed for experimenting with how notification management policies and other system functionalities can be linked to task structure.
---
paper_title: PrefMiner: mining user's preferences for intelligent mobile notification management

paper_content:

Mobile notifications are increasingly used by a variety of applications to inform users about events, news or just to send alerts and reminders to them. However, many notifications are neither useful nor relevant to users' interests and, also for this reason, they are considered disruptive and potentially annoying. In this paper we present the design, implementation and evaluation of PrefMiner, a novel interruptibility management solution that learns users' preferences for receiving notifications based on automatic extraction of rules by mining their interaction with mobile phones. The goal is to build a system that is intelligible for users, i.e., not just a "black-box" solution. Rules are shown to users who might decide to accept or discard them at run-time. The design of PrefMiner is based on a large scale mobile notification dataset and its effectiveness is evaluated by means of an in-the-wild deployment.
---
paper_title: Large-scale assessment of mobile notifications

paper_content:

Notifications are a core feature of mobile phones. They inform users about a variety of events. Users may take immediate action or ignore them depending on the importance of a notification as well as their current context. The nature of notifications is manifold, applications use them both sparsely and frequently. In this paper we present the first large-scale analysis of mobile notifications with a focus on users' subjective perceptions. We derive a holistic picture of notifications on mobile phones by collecting close to 200 million notifications from more than 40,000 users. Using a data-driven approach, we break down what users like and dislike about notifications. Our results reveal differences in importance of notifications and how users value notifications from messaging apps as well as notifications that include information about people and events. Based on these results we derive a number of findings about the nature of notifications and guidelines to effectively use them.
---
paper_title: I've got 99 problems, but vibration ain't one: a survey of smartphone users' concerns

paper_content:

Smartphone operating systems warn users when third-party applications try to access sensitive functions or data. However, all of the major smartphone platforms warn users about different application actions. To our knowledge, their selection of warnings was not grounded in user research; past research on mobile privacy has focused exclusively on the risks pertained to sharing location. To expand the scope of smartphone security and privacy research, we surveyed 3,115 smartphone users about 99 risks associated with 54 smartphone privileges. We asked participants to rate how upset they would be if given risks occurred and used this data to rank risks by levels of user concern. We then asked 41 smartphone users to discuss the risks in their own words; their responses confirmed that people find the lowest-ranked risks merely annoying but might seek legal or financial retribution for the highest-ranked risks. In order to determine the relative frequency of risks, we also surveyed the 3,115 users about experiences with "misbehaving" applications. Our ranking and frequency data can be used to guide the selection of warnings on smartphone platforms.
---
paper_title: Effects of Content and Time of Delivery on Receptivity to Mobile Interruptions

paper_content:

In this paper we investigate effects of the content of interruptions and of the time of interruption delivery on mobile phones. We review related work and report on a naturalistic quasi-experiment using experience-sampling that showed that the receptivity to an interruption is influenced by its content rather than by its time of delivery in the employed modality of delivery - SMS. We also examined the underlying variables that increase the perceived quality of content and found that the factors interest, entertainment, relevance and actionability influence people's receptivity significantly. Our findings inform system design that seeks to provide context-sensitive information or to predict interruptibility and suggest the consideration of receptivity as an extension to the way we think and reason about interruptibility.
---
paper_title: An in-situ study of mobile phone notifications

paper_content:

Notifications on mobile phones alert users about new messages, emails, social network updates, and other events. However, little is understood about the nature and effect of such notifications on the daily lives of mobile users. We report from a one-week, in-situ study involving 15 mobile phones users, where we collected real-world notifications through a smartphone logging application alongside subjective perceptions of those notifications through an online diary. We found that our participants had to deal with 63.5 notifications on average per day, mostly from messengers and email. Whether the phone is in silent mode or not, notifications were typically viewed within minutes. Social pressure in personal communication was amongst the main reasons given. While an increasing number of notifications was associated with an increase in negative emotions, receiving more messages and social network updates also made our participants feel more connected with others. Our findings imply that avoiding interruptions from notifications may be viable for professional communication, while in personal communication, approaches should focus on managing expectations.
---
paper_title: Notifications and awareness: a field study of alert usage and preferences

paper_content:

Desktop notifications are designed to provide awareness of information while a user is attending to a primary task. Unfortunately the awareness can come with the price of disruption to the focal task. We review results of a field study on the use and perceived value of email notifications in the workplace. We recorded users' interactions with software applications for two weeks and studied how notifications or their forced absence influenced users' quest for awareness of new email arrival, as well as the impact of notifications on their overall task focus. Results showed that users view notifications as a mechanism to provide passive awareness rather than a trigger to switch tasks. Turing off notifications cause some users to self interrupt more to explicitly monitor email arrival, while others appear to be able to better focus on their tasks. Users acknowledge notifications as disruptive, yet opt for them because of their perceived value in providing awareness.
---
paper_title: My Phone and Me: Understanding People's Receptivity to Mobile Notifications

paper_content:

Notifications are extremely beneficial to users, but they often demand their attention at inappropriate moments. In this paper we present an in-situ study of mobile interruptibility focusing on the effect of cognitive and physical factors on the response time and the disruption perceived from a notification. Through a mixed method of automated smartphone logging and experience sampling we collected 10372 in-the-wild notifications and 474 questionnaire responses on notification perception from 20 users. We found that the response time and the perceived disruption from a notification can be influenced by its presentation, alert type, sender-recipient relationship as well as the type, completion level and complexity of the task in which the user is engaged. We found that even a notification that contains important or useful content can cause disruption. Finally, we observe the substantial role of the psychological traits of the individuals on the response time and the disruption perceived from a notification.
---
paper_title: Large-scale assessment of mobile notifications

paper_content:

Notifications are a core feature of mobile phones. They inform users about a variety of events. Users may take immediate action or ignore them depending on the importance of a notification as well as their current context. The nature of notifications is manifold, applications use them both sparsely and frequently. In this paper we present the first large-scale analysis of mobile notifications with a focus on users' subjective perceptions. We derive a holistic picture of notifications on mobile phones by collecting close to 200 million notifications from more than 40,000 users. Using a data-driven approach, we break down what users like and dislike about notifications. Our results reveal differences in importance of notifications and how users value notifications from messaging apps as well as notifications that include information about people and events. Based on these results we derive a number of findings about the nature of notifications and guidelines to effectively use them.
---
paper_title: Managing Smartphone Interruptions through Adaptive Modes and Modulation of Notifications

paper_content:

Smartphones are capable of alerting their users to different kinds of digital interruption using different modalities and with varying modulation. Smart notification is the capability of a smartphone for selecting the user's preferred kind of alert in particular situations using the full vocabulary of notification modalities and modulations. It therefore goes well beyond attempts to predict if or when to silence a ringing phone call. We demonstrate smart notification for messages received from a document retrieval system while the user is attending a meeting. The notification manager learns about their notification preferences from users' judgements about videos of meetings. It takes account of the relevance of the interruption to the meeting, whether the user is busy and the sensed location of the smartphone. Through repeated training, the notification manager learns to reliably predict the preferred notification modes for users and this learning continues to improve with use.
---
paper_title: Investigating episodes of mobile phone activity as indicators of opportune moments to deliver notifications

paper_content:

We investigate whether opportune moments to deliver notifications surface at the endings of episodes of mobile interaction (making voice calls or receiving SMS) based on the assumption that the endings collocate with naturally occurring breakpoint in the user's primary task. Testing this with a naturalistic experiment we find that interruptions (notifications) are attended to and dealt with significantly more quickly after a user has finished an episode of mobile interaction compared to a random baseline condition, supporting the potential utility of this notification strategy. We also find that the workload and situational appropriateness of the secondary interruption task significantly affect subsequent delay and completion rate of the tasks. In situ self-reports and interviews reveal complexities in the subjective experience of the interruption, which suggest that a more nuanced classification of the particular call or SMS and its relationship to the primary task(s) would be desirable.
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paper_title: Investigating Mobile Users' Ringer Mode Usage and Attentiveness and Responsiveness to Communication

paper_content:

Smartphones are considered to be "always on, always connected" but mobile users are not always attentive and responsive to incoming communication. We present a mixed methods study investigating how mobile users use ringer modes for managing interruption by and awareness of incoming communication, and how these practices and locales affect their attentiveness and responsiveness. We show that mobile users have diverse ringer mode usage, but they switch ringer modes mainly for three purposes: avoiding interruption, preventing the phone from disrupting the environment, and noticing important notifications. In addition, without signals of notifications, users are less likely to immediately attend to notifications, but they are not less responsive to those they have attended. Finally, ringer mode switches, attentiveness, and responsiveness are all correlated with certain locales. We discuss implications from these findings, and suggest how future CMC tools and notification services take different purposes for using ringer modes and locales into consideration.
---
paper_title: MyTraces: Investigating Correlation and Causation between Users’ Emotional States and Mobile Phone Interaction

paper_content:

Most of the existing work concerning the analysis of emotional states and mobile phone interaction has been based on correlation analysis. In this paper, for the first time, we carry out a causality study to investigate the causal links between users’ emotional states and their interaction with mobile phones, which could provide valuable information to practitioners and researchers. The analysis is based on a dataset collected in-the-wild. We recorded 5,118 mood reports from 28 users over a period of 20 days. Our results show that users’ emotions have a causal impact on different aspects of mobile phone interaction. On the other hand, we can observe a causal impact of the use of specific applications, reflecting the external users’ context, such as socializing and traveling, on happiness and stress level. This study has profound implications for the design of interactive mobile systems since it identifies the dimensions that have causal effects on users’ interaction with mobile phones and vice versa. These findings might lead to the design of more effective computing systems and services that rely on the analysis of the emotional state of users, for example for marketing and digital health applications.
---
paper_title: Assessing the Relationship between Technical Affinity, Stress and Notifications on Smartphones

paper_content:

Smartphones have become an indispensable part of everyday life. By this time, push notifications are at the core of many apps, proactively pushing new content to users. These notifications may raise awareness, but also have the downside of being disruptive. In this paper we present a laboratory study investigating users' attitudes towards notifications and how they deal with notification settings on their smartphones. Permission requests for sending push notifications on iOS don't inform the user about the nature of notifications of this app, leaving the user to make a rather uninformed choice on whether to accept or deny. We show that requests including explanations are significantly more likely to be accepted. Our results further indicate that apart from being disruptive, notifications may create stress due to information overload. Notification settings, once assigned a preset, are rarely changed, although not necessarily matching the favored one.
---
paper_title: I've got 99 problems, but vibration ain't one: a survey of smartphone users' concerns

paper_content:

Smartphone operating systems warn users when third-party applications try to access sensitive functions or data. However, all of the major smartphone platforms warn users about different application actions. To our knowledge, their selection of warnings was not grounded in user research; past research on mobile privacy has focused exclusively on the risks pertained to sharing location. To expand the scope of smartphone security and privacy research, we surveyed 3,115 smartphone users about 99 risks associated with 54 smartphone privileges. We asked participants to rate how upset they would be if given risks occurred and used this data to rank risks by levels of user concern. We then asked 41 smartphone users to discuss the risks in their own words; their responses confirmed that people find the lowest-ranked risks merely annoying but might seek legal or financial retribution for the highest-ranked risks. In order to determine the relative frequency of risks, we also surveyed the 3,115 users about experiences with "misbehaving" applications. Our ranking and frequency data can be used to guide the selection of warnings on smartphone platforms.
---
paper_title: Effects of Content and Time of Delivery on Receptivity to Mobile Interruptions

paper_content:

In this paper we investigate effects of the content of interruptions and of the time of interruption delivery on mobile phones. We review related work and report on a naturalistic quasi-experiment using experience-sampling that showed that the receptivity to an interruption is influenced by its content rather than by its time of delivery in the employed modality of delivery - SMS. We also examined the underlying variables that increase the perceived quality of content and found that the factors interest, entertainment, relevance and actionability influence people's receptivity significantly. Our findings inform system design that seeks to provide context-sensitive information or to predict interruptibility and suggest the consideration of receptivity as an extension to the way we think and reason about interruptibility.
---
paper_title: An in-situ study of mobile phone notifications

paper_content:

Notifications on mobile phones alert users about new messages, emails, social network updates, and other events. However, little is understood about the nature and effect of such notifications on the daily lives of mobile users. We report from a one-week, in-situ study involving 15 mobile phones users, where we collected real-world notifications through a smartphone logging application alongside subjective perceptions of those notifications through an online diary. We found that our participants had to deal with 63.5 notifications on average per day, mostly from messengers and email. Whether the phone is in silent mode or not, notifications were typically viewed within minutes. Social pressure in personal communication was amongst the main reasons given. While an increasing number of notifications was associated with an increase in negative emotions, receiving more messages and social network updates also made our participants feel more connected with others. Our findings imply that avoiding interruptions from notifications may be viable for professional communication, while in personal communication, approaches should focus on managing expectations.
---
paper_title: Designing content-driven intelligent notification mechanisms for mobile applications

paper_content:

An increasing number of notifications demanding the smartphone user's attention, often arrive at an inappropriate moment, or carry irrelevant content. In this paper we present a study of mobile user interruptibility with respect to notification content, its sender, and the context in which a notification is received. In a real-world study we collect around 70,000 instances of notifications from 35 users. We group notifications according to the applications that initiated them, and the social relationship between the sender and the receiver. Then, by considering both content and context information, such as the current activity of a user, we discuss the design of classifiers for learning the most opportune moment for the delivery of a notification carrying a specific type of information. Our results show that such classifiers lead to a more accurate prediction of users' interruptibility than an alternative approach based on user-defined rules of their own interruptibility.
---
paper_title: Notifications and awareness: a field study of alert usage and preferences

paper_content:

Desktop notifications are designed to provide awareness of information while a user is attending to a primary task. Unfortunately the awareness can come with the price of disruption to the focal task. We review results of a field study on the use and perceived value of email notifications in the workplace. We recorded users' interactions with software applications for two weeks and studied how notifications or their forced absence influenced users' quest for awareness of new email arrival, as well as the impact of notifications on their overall task focus. Results showed that users view notifications as a mechanism to provide passive awareness rather than a trigger to switch tasks. Turing off notifications cause some users to self interrupt more to explicitly monitor email arrival, while others appear to be able to better focus on their tasks. Users acknowledge notifications as disruptive, yet opt for them because of their perceived value in providing awareness.
---
paper_title: PrefMiner: mining user's preferences for intelligent mobile notification management

paper_content:

Mobile notifications are increasingly used by a variety of applications to inform users about events, news or just to send alerts and reminders to them. However, many notifications are neither useful nor relevant to users' interests and, also for this reason, they are considered disruptive and potentially annoying. In this paper we present the design, implementation and evaluation of PrefMiner, a novel interruptibility management solution that learns users' preferences for receiving notifications based on automatic extraction of rules by mining their interaction with mobile phones. The goal is to build a system that is intelligible for users, i.e., not just a "black-box" solution. Rules are shown to users who might decide to accept or discard them at run-time. The design of PrefMiner is based on a large scale mobile notification dataset and its effectiveness is evaluated by means of an in-the-wild deployment.
---
paper_title: Interpretable Machine Learning for Mobile Notification Management: An Overview of PrefMiner

paper_content:

Mobile notifications are increasingly used by a variety of applications to inform users about events, news or just to send alerts and reminders to them. However, many notifications are neither useful nor relevant to users' interests and, for this reason, they are considered disruptive and potentially annoying, as well. PrefMiner is a novel interruptibility management solution that learns users' preferences for receiving notifications based on automatic extraction of rules by mining their interaction with mobile phones. PrefMiner aims at being intelligible and interpretable for users, i.e., not just a "black box" solution, by suggesting rules to users who might decide to accept or discard them at run-time. The design of PrefMiner is based on a large scale mobile notification dataset and its effectiveness is evaluated by means of an in-the-wild deployment.
---
paper_title: My Phone and Me: Understanding People's Receptivity to Mobile Notifications

paper_content:

Notifications are extremely beneficial to users, but they often demand their attention at inappropriate moments. In this paper we present an in-situ study of mobile interruptibility focusing on the effect of cognitive and physical factors on the response time and the disruption perceived from a notification. Through a mixed method of automated smartphone logging and experience sampling we collected 10372 in-the-wild notifications and 474 questionnaire responses on notification perception from 20 users. We found that the response time and the perceived disruption from a notification can be influenced by its presentation, alert type, sender-recipient relationship as well as the type, completion level and complexity of the task in which the user is engaged. We found that even a notification that contains important or useful content can cause disruption. Finally, we observe the substantial role of the psychological traits of the individuals on the response time and the disruption perceived from a notification.
---
paper_title: Large-scale assessment of mobile notifications

paper_content:

Notifications are a core feature of mobile phones. They inform users about a variety of events. Users may take immediate action or ignore them depending on the importance of a notification as well as their current context. The nature of notifications is manifold, applications use them both sparsely and frequently. In this paper we present the first large-scale analysis of mobile notifications with a focus on users' subjective perceptions. We derive a holistic picture of notifications on mobile phones by collecting close to 200 million notifications from more than 40,000 users. Using a data-driven approach, we break down what users like and dislike about notifications. Our results reveal differences in importance of notifications and how users value notifications from messaging apps as well as notifications that include information about people and events. Based on these results we derive a number of findings about the nature of notifications and guidelines to effectively use them.
---
paper_title: InterruptMe: designing intelligent prompting mechanisms for pervasive applications

paper_content:

The mobile phone represents a unique platform for interactive applications that can harness the opportunity of an immediate contact with a user in order to increase the impact of the delivered information. However, this accessibility does not necessarily translate to reachability, as recipients might refuse an initiated contact or disfavor a message that comes in an inappropriate moment. In this paper we seek to answer whether, and how, suitable moments for interruption can be identified and utilized in a mobile system. We gather and analyze a real-world smartphone data trace and show that users' broader context, including their activity, location, time of day, emotions and engagement, determine different aspects of interruptibility. We then design and implement InterruptMe, an interruption management library for Android smartphones. An extensive experiment shows that, compared to a context-unaware approach, interruptions elicited through our library result in increased user satisfaction and shorter response times.
---
paper_title: Didn't you see my message?: predicting attentiveness to mobile instant messages

paper_content:

Mobile instant messaging (e.g., via SMS or WhatsApp) often goes along with an expectation of high attentiveness, i.e., that the receiver will notice and read the message within a few minutes. Hence, existing instant messaging services for mobile phones share indicators of availability, such as the last time the user has been online. However, in this paper we not only provide evidence that these cues create social pressure, but that they are also weak predictors of attentiveness. As remedy, we propose to share a machine-computed prediction of whether the user will view a message within the next few minutes or not. For two weeks, we collected behavioral data from 24 users of mobile instant messaging services. By the means of machine-learning techniques, we identified that simple features extracted from the phone, such as the user's interaction with the notification center, the screen activity, the proximity sensor, and the ringer mode, are strong predictors of how quickly the user will attend to the messages. With seven automatically selected features our model predicts whether a phone user will view a message within a few minutes with 70.6% accuracy and a precision for fast attendance of 81.2%
---
paper_title: Ask, but don't interrupt: the case for interruptibility-aware mobile experience sampling

paper_content:

The mobile phone-based Experience Sampling Method (ESM) enables in situ recording of human behaviour and experience by querying users, via their smartphones, anywhere and anytime. Sampling can happen on a previously unimaginable scale, and across a diverse pool of participants. Therefore, mobile ESM is not limited to capturing users' manual responses, as the surrounding context can be automatically captured by mobile sensors. However, obtaining high quality data with ESM is challenging, as users may fail to respond honestly, or may even ignore the questionnaire prompts if they perceive the study as too burdensome. In this paper, we discuss the potential of using interruptibility prediction models to deliver mobile ESM questionnaires at opportune moments, and thus improve the effectiveness of a study. We examine context prediction and interruptibility inference, which are fundamental challenges that need we need to overcome in order to make mobile ESMs better aligned with a user's lifestyle, and consequently paint a truthful picture of a user's behaviour.
---
paper_title: Understanding the Role of Places and Activities on Mobile Phone Interaction and Usage Patterns

paper_content:

User interaction patterns with mobile apps and notifications are generally complex due to the many factors involved. However a deep understanding of what influences them can lead to more acceptable applications that are able to deliver information at the right time. In this paper, we present for the first time an in-depth analysis of interaction behavior with notifications in relation to the location and activity of users. We conducted an in-situ study for a period of two weeks to collect more than 36,000 notifications, 17,000 instances of application usage, 77,000 location samples, and 487 days of daily activity entries from 26 students at a UK university. Our results show that users’ attention towards new notifications and willingness to accept them are strongly linked to the location they are in and in minor part to their current activity. We consider both users’ receptivity and attentiveness, and we show that different response behaviors are associated to different locations. These findings are fundamental from a design perspective since they allow us to understand how certain types of places are linked to specific types of interaction behavior. This information can be used as a basis for the development of novel intelligent mobile applications and services.
---
paper_title: Instant Messaging and Interruption : Influence of Task Type on Performance

paper_content:

We describe research on the effects of instant messaging (IM) on ongoing computing tasks. We present a study that builds on earlier work exploring the influence of sending notifications at different times and the kinds of tasks that are particularly susceptible to interruption. This work investigates alternative hypotheses about the nature of disruption for a list evaluation task, an activity we had identified as being particularly costly to interrupt. Our findings replicate earlier work, showing the generally harmful effects of IM, and further show that notifications are more disruptive for fast, stimulus-driven search tasks than for slower, more effortful semantic-based search tasks.
---
paper_title: Leveraging characteristics of task structure to predict the cost of interruption

paper_content:

A challenge in building interruption reasoning systems is to compute an accurate cost of interruption (COI). Prior work has used interface events and other cues to predict COI, but ignore characteristics related to the structure of a task. This work investigates how well characteristics of task structure can predict COI, as objectively measured by resumption lag. In an experiment, users were interrupted during task execution at various boundaries to collect a large sample of resumption lag values. Statistical methods were employed to create a parsimonious model that uses characteristics of task structure to predict COI. A subsequent experiment with different tasks showed that the model can predict COI with reasonably high accuracy. Our model can be expediently applied to many goal-directed tasks, allowing systems to make more effective decisions about when to interrupt.
---
paper_title: Designing content-driven intelligent notification mechanisms for mobile applications

paper_content:

An increasing number of notifications demanding the smartphone user's attention, often arrive at an inappropriate moment, or carry irrelevant content. In this paper we present a study of mobile user interruptibility with respect to notification content, its sender, and the context in which a notification is received. In a real-world study we collect around 70,000 instances of notifications from 35 users. We group notifications according to the applications that initiated them, and the social relationship between the sender and the receiver. Then, by considering both content and context information, such as the current activity of a user, we discuss the design of classifiers for learning the most opportune moment for the delivery of a notification carrying a specific type of information. Our results show that such classifiers lead to a more accurate prediction of users' interruptibility than an alternative approach based on user-defined rules of their own interruptibility.
---
paper_title: Notifications and awareness: a field study of alert usage and preferences

paper_content:

Desktop notifications are designed to provide awareness of information while a user is attending to a primary task. Unfortunately the awareness can come with the price of disruption to the focal task. We review results of a field study on the use and perceived value of email notifications in the workplace. We recorded users' interactions with software applications for two weeks and studied how notifications or their forced absence influenced users' quest for awareness of new email arrival, as well as the impact of notifications on their overall task focus. Results showed that users view notifications as a mechanism to provide passive awareness rather than a trigger to switch tasks. Turing off notifications cause some users to self interrupt more to explicitly monitor email arrival, while others appear to be able to better focus on their tasks. Users acknowledge notifications as disruptive, yet opt for them because of their perceived value in providing awareness.
---
paper_title: NextPlace: A Spatio-Temporal Prediction Framework for Pervasive Systems

paper_content:

Accurate and fine-grained prediction of future user location and geographical profile has interesting and promising applications including targeted content service, advertisement dissemination for mobile users, and recreational social networking tools for smart-phones. Existing techniques based on linear and probabilistic models are not able to provide accurate prediction of the location patterns from a spatio-temporal perspective, especially for long-term estimation. More specifically, they are able to only forecast the next location of a user, but not his/her arrival time and residence time, i.e., the interval of time spent in that location. Moreover, these techniques are often based on prediction models that are not able to extend predictions further in the future. ::: ::: In this paper we present NextPlace, a novel approach to location prediction based on nonlinear time series analysis of the arrival and residence times of users in relevant places. NextPlace focuses on the predictability of single users when they visit their most important places, rather than on the transitions between different locations. We report about our evaluation using four different datasets and we compare our forecasting results to those obtained by means of the prediction techniques proposed in the literature. We show how we achieve higher performance compared to other predictors and also more stability over time, with an overall prediction precision of up to 90% and a performance increment of at least 50% with respect to the state of the art.
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paper_title: BusyBody: creating and fielding personalized models of the cost of interruption

paper_content:

Interest has been growing in opportunities to build and deploy statistical models that can infer a computer user's current interruptability from computer activity and relevant contextual information. We describe a system that intermittently asks users to assess their perceived interruptability during a training phase and that builds decision-theoretic models with the ability to predict the cost of interrupting the user. The models are used at run-time to compute the expected cost of interruptions, providing a mediator for incoming notifications, based on a consideration of a user's current and recent history of computer activity, meeting status, location, time of day, and whether a conversation is detected.
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paper_title: Notification, Disruption, and Memory: Effects of Messaging Interruptions on Memory and Performance

paper_content:

We describe a study on the influence of instant messaging (IM) on ongoing computing tasks. The study both replicates and extends earlier work on the cost of sending notifications at different times and the sensitivity of different tasks to interruption. We investigate alternative hypotheses about the nature of disruption for a list evaluation task, an activity identified as being particularly costly to interrupt. Our findings once again show the generally disruptive effects of IM, especially during fast, stimulus-driven search tasks. In addition, we show that interruptions coming early during a search task are more likely to result in the user forgetting the primary task goal than interruptions that arrive later on. These findings have implications for the design of user interfaces and notification policies that minimize the disruptiveness of notifications.
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paper_title: Using context-aware computing to reduce the perceived burden of interruptions from mobile devices

paper_content:

The potential for sensor-enabled mobile devices to proactively present information when and where users need it ranks among the greatest promises of ubiquitous computing. Unfortunately, mobile phones, PDAs, and other computing devices that compete for the user's attention can contribute to interruption irritability and feelings of information overload. Designers of mobile computing interfaces, therefore, require strategies for minimizing the perceived interruption burden of proactively delivered messages. In this work, a context-aware mobile computing device was developed that automatically detects postural and ambulatory activity transitions in real time using wireless accelerometers. This device was used to experimentally measure the receptivity to interruptions delivered at activity transitions relative to those delivered at random times. Messages delivered at activity transitions were found to be better received, thereby suggesting a viable strategy for context-aware message delivery in sensor-enabled mobile computing devices.
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paper_title: PrefMiner: mining user's preferences for intelligent mobile notification management

paper_content:

Mobile notifications are increasingly used by a variety of applications to inform users about events, news or just to send alerts and reminders to them. However, many notifications are neither useful nor relevant to users' interests and, also for this reason, they are considered disruptive and potentially annoying. In this paper we present the design, implementation and evaluation of PrefMiner, a novel interruptibility management solution that learns users' preferences for receiving notifications based on automatic extraction of rules by mining their interaction with mobile phones. The goal is to build a system that is intelligible for users, i.e., not just a "black-box" solution. Rules are shown to users who might decide to accept or discard them at run-time. The design of PrefMiner is based on a large scale mobile notification dataset and its effectiveness is evaluated by means of an in-the-wild deployment.
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paper_title: In-situ investigation of notifications in multi-device environments

paper_content:

Smart devices have arrived in our everyday lives. Being able to notify the user about events is a core feature of these devices. Related work investigated interruptions caused by notifications on single devices. In this paper, we investigate notifications in multi-device environments by analyzing the results of a week-long in-situ study with 16 participants. We used the Experience Sampling Method (ESM) and recorded the participants' interaction with smartphones, smartwatches, tablets and PCs. Disregarding the type or content of notifications, we found that the smartphone is the preferred device on which to be notified. Further, we found that the proximity to the device, whether it is currently being used and the user's current location can be used to predict if the user wants to receive notifications on a device. The findings can be used to design future multi-device aware smart notification systems.
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paper_title: I'll be there for you: Quantifying Attentiveness towards Mobile Messaging

paper_content:

Social norm has it that people are expected to respond to mobile phone messages quickly. We investigate how attentive people really are and how timely they actually check and triage new messages throughout the day. By collecting more than 55,000 messages from 42 mobile phone users over the course of two weeks, we were able to predict people's attentiveness through their mobile phone usage with close to 80% accuracy. We found that people were attentive to messages 12.1 hours a day, i.e. 84.8 hours per week, and provide statistical evidence how very short people's inattentiveness lasts: in 75% of the cases mobile phone users return to their attentive state within 5 minutes. In this paper, we present a comprehensive analysis of attentiveness throughout each hour of the day and show that intelligent notification delivery services, such as bounded deferral, can assume that inattentiveness will be rare and subside quickly.
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paper_title: Towards attention-aware adaptive notification on smart phones

paper_content:

As the amount of information to users increases with the trends of an increasing numbers of devices, applications, and web services, the new bottleneck in computing is human attention. To minimize users attentional overload, we propose a novel middleware "Attelia" that detects breakpoints of user's mobile interactions to deliver notifications adaptively. Attelia detects such timings in real-time, using only users phones, without any external sensors, and without any modifications to applications. Our extensive evaluation proved Attelias effectiveness. In-the-wild user study with 30 participants for 16 days showed that, specifically for the users with greater sensitivity for interruptive notification timings, notification scheduling in Attelia's breakpoint timing reduced users frustration by 28% in users' real smart phone environments.
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paper_title: Attention-Sensitive Alerting

paper_content:

We introduce utility-directed procedures for mediating the flow of potentially distracting alerts and communications to computer users. We present models and inference procedures that balance the context-sensitive costs of deferring alerts with the cost of interruption. We describe the challenge of reasoning about such costs under uncertainty via an analysis of user activity and the content of notifications. After introducing principles of attention-sensitive alerting, we focus on the problem of guiding alerts about email messages. We dwell on the problem of inferring the expected criticality of email and discuss work on the PRIORITIES system, centering on prioritizing email by criticality and modulating the communication of notifications to users about the presence and nature of incoming email.
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paper_title: Investigating episodes of mobile phone activity as indicators of opportune moments to deliver notifications

paper_content:

We investigate whether opportune moments to deliver notifications surface at the endings of episodes of mobile interaction (making voice calls or receiving SMS) based on the assumption that the endings collocate with naturally occurring breakpoint in the user's primary task. Testing this with a naturalistic experiment we find that interruptions (notifications) are attended to and dealt with significantly more quickly after a user has finished an episode of mobile interaction compared to a random baseline condition, supporting the potential utility of this notification strategy. We also find that the workload and situational appropriateness of the secondary interruption task significantly affect subsequent delay and completion rate of the tasks. In situ self-reports and interviews reveal complexities in the subjective experience of the interruption, which suggest that a more nuanced classification of the particular call or SMS and its relationship to the primary task(s) would be desirable.
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paper_title: If not now, when?: the effects of interruption at different moments within task execution

paper_content:

User attention is a scarce resource, and users are susceptible to interruption overload. Systems do not reason about the effects of interrupting a user during a task sequence. In this study, we measure effects of interrupting a user at different moments within task execution in terms of task performance, emotional state, and social attribution. Task models were developed using event perception techniques, and the resulting models were used to identify interruption timings based on a user's predicted cognitive load. Our results show that different interruption moments have different impacts on user emotional state and positive social attribution, and suggest that a system could enable a user to maintain a high level of awareness while mitigating the disruptive effects of interruption. We discuss implications of these results for the design of an attention manager.
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paper_title: Mobile User Research: A Practical Guide

paper_content:

This book will give you a practical overview of several methods and approaches for designing mobile technologies and conducting mobile user research, including how to understand behavior and evaluate how such technologies are being (or may be) used out in the world. Each chapter includes case studies from our own work and highlights advantages, limitations, and very practical steps that should be taken to increase the validity of the studies you conduct and the data you collect. This book is intended as a practical guide for conducting mobile research focused on the user and their experience. We hope that the depth and breadth of case studies presented, as well as specific best practices, will help you to design the best technologies possible and choose appropriate methods to gather ethical, reliable, and generalizable data to explore the use of mobile technologies out in the world.
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paper_title: A method, system, and tools for intelligent interruption management

paper_content:

Interrupting users engaged in tasks typically has negative effects on their task completion time, error rate, and affective state. Empirical research has shown that these negative effects can be mitigated by deferring interruptions until more opportune moments in a user's task sequence. However, existing systems that reason about when to interrupt do not have access to task models that would allow for such finer-grained temporal reasoning. We outline our method of finding opportune moments that links a physiological measure of workload with task modeling techniques and theories of attention. We describe the design and implementation of our interruption management system, showing how it can be used to specify and monitor practical, representative user tasks. We discuss our ongoing empirical work in this area, and how the use of our framework may enable attention aware systems to consider a user's position in a task when reasoning about when to interrupt.
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paper_title: The attentional costs of interrupting task performance at various stages

paper_content:

Abstract : The visual occlusion technique has received considerable attention in recent years as a method for measuring the interruptible aspects of in-vehicle information system (IVIS) task performance. Because the visual occlusion technique lacks a loading task during "occluded" periods, an alternate method was adopted to provide increased sensitivity to the attentional costs of interruptions on IVIS-style task performance. Participants alternated between performing a VCR programming task and a simple tracking task. Results indicate that it does matter at which point the VCR task is interrupted in terms of time to resume the VCR task. Specifically, the resumption time, or lag, was lowest right before beginning a new task stage such as entering the show end-time, or when performing a repetitive scrolling task. The results suggest that it might be appropriate to include measures of resumption lag when testing the interruptability of IVIS-style tasks.
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paper_title: Human Behavior On the need for attention-aware systems : Measuring effects of interruption on task performance , error rate , and affective state

paper_content:

Abstract This paper reports results from a controlled experiment ( N = 50) measuring effects of interruption on task completion time, error rate, annoyance, and anxiety. The experiment used a sample of primary and peripheral tasks representative of those often performed by users. Our experiment differs from prior interruption experiments because it measures effects of interrupting a user’s tasks along both performance and affective dimensions and controls for task workload by manipulating only the time at which peripheral tasks were displayed – between vs. during the execution of primary tasks. Results show that when peripheral tasks interrupt the execution of primary tasks, users require from 3% to 27% more time to complete the tasks, commit twice the number of errors across tasks, experience from 31% to 106% more annoyance, and experience twice the increase in anxiety than when those same peripheral tasks are presented at the boundary between primary tasks. An important implication of our work is that attention-aware systems could mitigate effects of interruption by deferring presentation of peripheral information until coarse boundaries are reached during task execution. As our results show, deferring presentation for a short time, i.e. just a few seconds, can lead to a large mitigation of disruption.
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Title: Intelligent Notification Systems: A Survey of the State of the Art and Research Challenges

Section 1: INTRODUCTION
Description 1: This section introduces the role of mobile phones in daily life, the importance of notifications, and the key issues around unwanted interruptions and notification management.

Section 2: Definitions of Interruptions from Different Research Fields
Description 2: This section discusses various definitions and interpretations of interruptions from different disciplines, including linguistics, psychology, and computer science.

Section 3: Types of Interruptions
Description 3: This section categorizes and explains different types of interruptions, distinguishing between internal and external interruptions and further classifying external ones into implicit and explicit interruptions.

Section 4: Definition of Interruptions in Context of this Survey
Description 4: This section provides a definition of interruptions tailored to the survey's focus on external interruptions in desktop and mobile environments.

Section 5: Sources of Interruptions
Description 5: This section discusses various sources of interruptions in both human-human discourse and human-computer interaction.

Section 6: COST OF INTERRUPTION
Description 6: This section explores the detrimental effects of interruptions on memory, task completion, error rates, emotional state, and user experience.

Section 7: INDIVIDUAL DIFFERENCES IN PERCEIVING INTERRUPTIONS
Description 7: This section delves into individual variability in handling interruptions and multitasking, highlighting factors like motivation, anxiety, and cognitive style.

Section 8: INTERRUPTIBILITY MANAGEMENT
Description 8: This section defines interruptibility management, discusses attentiveness and receptivity to interruptions, and presents an overview of methods to build interruptibility models.

Section 9: INTERRUPTIBILITY MANAGEMENT IN DESKTOP ENVIRONMENTS
Description 9: This section reviews research on managing interruptions in desktop settings, including using sensor data, task phases, and real-time inferences.

Section 10: INTERRUPTIBILITY MANAGEMENT IN MOBILE ENVIRONMENTS
Description 10: This section discusses interruptibility management for mobile devices, focusing on user perception, filtering irrelevant information, and utilizing contextual data.

Section 11: LIMITATIONS OF THE STATE OF THE ART AND OPEN CHALLENGES
Description 11: This section highlights the limitations of current interruptibility studies and outlines open research challenges, such as deferring notifications, monitoring cognitive context, and modeling for multiple devices.

Section 12: SUMMARY
Description 12: This section summarizes the survey's discussions, emphasizing the need for intelligent notification mechanisms and the future direction of research in this field.