Collective Intelligence in Humans: A Literature Review
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paper_title: Swarm intelligence in animals and humans.

paper_content:

Electronic media have unlocked a hitherto largely untapped potential for swarm intelligence (SI; generally, the realisation that group living can facilitate solving cognitive problems that go beyond the capacity of single animals) in humans with relevance for areas such as company management, prediction of elections, product development and the entertainment industry. SI is a rapidly developing topic that has become a hotbed for both innovative research and wild speculation. Here, we tie together approaches from seemingly disparate areas by means of a general definition of SI to unite SI work on both animal and human groups. Furthermore, we identify criteria that are important for SI to operate and propose areas in which further progress with SI research can be made.
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paper_title: Toward collective intelligence of online communities: A primitive conceptual model

paper_content:

Inspired by the ideas of Swarm Intelligence and the “global brain”, a concept of “community intelligence” is suggested in the present paper, reflecting that some “intelligent” features may emerge in a Web-mediated online community from interactions and knowledge-transmissions between the community members. This possible research field of community intelligence is then examined under the backgrounds of “community” and “intelligence” researches. Furthermore, a conceptual model of community intelligence is developed from two views. From the structural view, the community intelligent system is modeled as a knowledge supernetwork that is comprised of triple interwoven networks of the media network, the human network, and the knowledge network. Furthermore, based on a dyad of knowledge in two forms of “knowing” and “knoware”, the dynamic view describes the basic mechanics of the formation and evolution of “community intelligence”. A few relevant research issues are shortly discussed on the basis of the proposed conceptual model.
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paper_title: From social computing to reflexive collective intelligence: The IEML research program

paper_content:

The IEML research program promotes a radical innovation in the notation and processing of semantics. IEML (Information Economy MetaLanguage) is a regular language that provides new methods for semantic interoperability, semantic navigation, collective categorization and self-referential collective intelligence. This research program is compatible with the major standards of the Web of data and is in tune with the current trends in social computing. The paper explains the philosophical relevance of this new language, expounds its syntactic and semantic structures and ponders its possible implications for the growth of collective intelligence in cyberspace.
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paper_title: Collective Intelligence in the Organization of Science

paper_content:

Whereas some suggest that consensus is the desirable end goal in fields of science, this paper suggests that the existing literature on collective intelligence offers key alternative insights into the evolution of knowledge in scientific communities. Drawing on the papers in this special issue, we find that the papers fall across a spectrum of convergent, divergent, and reflective activities. In addition, we find there to be a set of ongoing theoretical tensions common across the papers. We suggest that this diversity of activities and ongoing theoretical tensions—both signs of collective intelligence— may be a far more appropriate measure than consensus of the health of a scientific community.
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paper_title: On model design for simulation of collective intelligence

paper_content:

The study of collective intelligence (CI) systems is increasingly gaining interest in a variety of research and application domains. Those domains range from existing research areas such as computer networks and collective robotics to upcoming areas of agent-based and insect-based computing; also including applications on the internet and in games and movies. CI systems are complex by nature and (1) are effectively adaptive in uncertain and unknown environments, (2) can organise themselves autonomously, and (3) exhibit 'emergent' behaviour. Among others, multi-agent systems, complex adaptive systems, swarm intelligence and self-organising systems are considered to be such systems. The explosive wild growth of research studies of CI systems has not yet led to a systematic approach for model design of these kinds of systems. Although there have been recent efforts on the issue of system design (the complete design trajectory from identifying system requirements up to implementation), the problem of choosing and specifying a good model of a CI system is often done implicitly and sometimes even completely ignored. The aim of this article is to bring to the attention that model design is an essential as well as an integral part of system design. We present a constructive approach to systematically design, build and test models of CI systems. Because simulation is often used as a way to research CI systems, we particularly focus on models that can be used for simulation. Additionally, we show that it is not necessary to re-invent the wheel: here, we show how existing models and algorithms can be used for CI model design. The approach is illustrated by means of two example studies on a (semi-automated) multi-player game and collaborative robotics.
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paper_title: A Learning Framework for Knowledge Building and Collective Wisdom Advancement in Virtual Learning Communities

paper_content:

This study represents an effort to construct a learning framework for knowledge building and collective wisdom advancement in a virtual learning community (VLC) from the perspectives of system wholeness, intelligence wholeness and dynamics, learning models, and knowledge management. It also tries to construct the zone of proximal development (ZPD) of VLCs based on the combination of Vygotsky’s theory of zone of proximal development and the trajectories of knowledge building. The aim of a VLC built on the theories of constructivism, situated learning, and knowledge building, etc., is to apply individual intelligence to online learning, bring the advantages of collaborative learning and collective wisdom into play, solve difficult problems in independent learning, and lead to the integration and sublimation of collective wisdom through long-term individual interactions, collaborative learning and knowledge building.
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paper_title: The Origin of Mind: Evolution of Brain, Cognition, and General Intelligence

paper_content:

Darwin considered an understanding of the evolution of the human mind and brain to be of major importance to the evolutionary sciences. This groundbreaking book sets out a comprehensive, integrated theory of why and how the human mind has developed to function as it does. Geary proposes that human motivational, affective, behavioral, and cognitive systems have evolved to process social and ecological information (e.g., facial expressions) that covaried with survival or reproductive options during human evolution. Further, he argues that the ultimate focus of all of these systems is to support our attempts to gain access to and control of resources - more specifically, the social (e.g., mates), biological (e.g., food), and physical (e.g., territory) resources that supported successful survival and reproduction over time. In this view, Darwin's conceptualization of natural selection as a "struggle for existence" becomes, for us, a struggle with other human beings for control of the available resources. This struggle provides a means of integrating modular brain and cognitive systems such as language with those brain and cognitive systems that support general intelligence. To support his arguments, Geary draws on an impressive array of recent findings in cognitive science and neuroscience as well as primatology, anthropology, and sociology. The book also explores a number of issues that are of interest in modern society, including how general intelligence relates to academic achievement, occupational status, and income. Readers will find this book a thought-provoking read and an impetus for new theories of mind.
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paper_title: The Business Model: Recent Developments and Future Research

paper_content:

This article provides a broad and multifaceted review of the received literature on business models in which the authors examine the business model concept through multiple subject-matter lenses. The review reveals that scholars do not agree on what a business model is and that the literature is developing largely in silos, according to the phenomena of interest of the respective researchers. However, the authors also found emerging common themes among scholars of business models. Specifically, (1) the business model is emerging as a new unit of analysis; (2) business models emphasize a system-level, holistic approach to explaining how firms “do business”; (3) firm activities play an important role in the various conceptualizations of business models that have been proposed; and (4) business models seek to explain how value is created, not just how it is captured. These emerging themes could serve as catalysts for a more unified study of business models.
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paper_title: Globalization, information and communication technologies, and the prospect of a ‘global village’: promises of inclusion or electronic colonization?

paper_content:

This paper discusses the reciprocal relationships among globalization, information and communication technologies (ICT), and the prospect of a ‘global village’. The current metaphor of a ‘global village’ (regardless of physical access to ICT) is problematic, and can be interpreted as a form of electronic colonization. However, through such concepts as blurred identity, nomadism, and hybridity, a distinctly (post‐modern) ICT landscape can be redrawn in a way that accepts the global identity of the ICT, but denies the colonial erasure associated with the global‐village narrative. ICT, in themselves, cannot serve as an end in education, but the demand for critical education involving ICT is pressing as the effects of globalization are experienced. Three methods of promoting decolonizing criticality are proposed: critical emotional literacy, collective witnessing, and collective intelligence.
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paper_title: On the Collective Nature of Human Intelligence

paper_content:

A fundamental assumption of cognitive science is that the individual is the correct unit of analysis for understanding human intelligence. I present evidence that this assumption may have limited utility, that the social networks containing the individuals are an important additional unit of analysis, and that this “network intelligence” is significantly mediated by non-linguistic processes. Across a broad range of situations these network effects typically predict 40% or more of the variation in human behavior.
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paper_title: Groups of diverse problem solvers can outperform groups of high-ability problem solvers

paper_content:

We introduce a general framework for modeling functionally diverse problem-solving agents. In this framework, problem-solving agents possess representations of problems and algorithms that they use to locate solutions. We use this framework to establish a result relevant to group composition. We find that when selecting a problem-solving team from a diverse population of intelligent agents, a team of randomly selected agents outperforms a team comprised of the best-performing agents. This result relies on the intuition that, as the initial pool of problem solvers becomes large, the best-performing agents necessarily become similar in the space of problem solvers. Their relatively greater ability is more than offset by their lack of problem-solving diversity.
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paper_title: How social influence can undermine the wisdom of crowd effect

paper_content:

Social groups can be remarkably smart and knowledgeable when their averaged judgements are compared with the judgements of individuals. Already Galton [Galton F (1907) Nature 75:7] found evidence that the median estimate of a group can be more accurate than estimates of experts. This wisdom of crowd effect was recently supported by examples from stock markets, political elections, and quiz shows [Surowiecki J (2004) The Wisdom of Crowds]. In contrast, we demonstrate by experimental evidence (N = 144) that even mild social influence can undermine the wisdom of crowd effect in simple estimation tasks. In the experiment, subjects could reconsider their response to factual questions after having received average or full information of the responses of other subjects. We compare subjects’ convergence of estimates and improvements in accuracy over five consecutive estimation periods with a control condition, in which no information about others’ responses was provided. Although groups are initially “wise,” knowledge about estimates of others narrows the diversity of opinions to such an extent that it undermines the wisdom of crowd effect in three different ways. The “social influence effect” diminishes the diversity of the crowd without improvements of its collective error. The “range reduction effect” moves the position of the truth to peripheral regions of the range of estimates so that the crowd becomes less reliable in providing expertise for external observers. The “confidence effect” boosts individuals’ confidence after convergence of their estimates despite lack of improved accuracy. Examples of the revealed mechanism range from misled elites to the recent global financial crisis.
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paper_title: Swarm intelligence in humans: diversity can trump ability

paper_content:

We identify some of the possibilities and limitations of human swarm intelligence (SI) using the response of the public to two types of cognitive problems. Furthermore, we propose a simple measure for the quantification of collective information that could form the basis for SI in study populations for specific tasks. Our three main results are (1) that the potential benefits of SI depend on the type of problem, (2) that individual performance and collective performance can be uncorrelated and that a group of individually high performers can be outcompeted by a same-size group of individually low performers, and (3) that adding diversity to a group can be more beneficial than adding expertise. Our results question the emphasis that societies and organizations can put on individual performance to the detriment of diversity as far as teams are concerned. Nevertheless, it is important to point out that while diversity is a necessary condition for effective SI, diversity alone is clearly not sufficient. Finally, we discuss the potential implications of our findings for the evolution of group composition and the maintenance of personality diversity in animals.
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paper_title: Collective intelligence for idea management with Internet‐based information aggregation markets

paper_content:

Purpose – The purpose of this paper is to explore the use of information aggregation markets (IAMs) for community‐based idea management and to present IDeM, a novel Internet‐based software tool that can be used for generating and evaluating new ideas utilizing the concept of IAMs.Design/methodology/approach – Starting with a review of existing methods for collective intelligence, IAMs are identified as a prominent method for collective intelligence. Specific requirements for exploring IAMs for idea management are derived. Based on these requirements, a software tool for implementing IAMs in the context of idea management is developed (IDeM). IDeM has been evaluated and evaluation results are used to identify IDeM's benefits and limitations. A review of related work points out the innovative characteristics of IDeM.Findings – Evaluation results indicate that IAMs is an efficient method for idea generation and evaluation. Moreover IDeM is perceived both as easy to use and efficient in supporting idea genera...
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paper_title: Towards knowledge management based on harnessing collective intelligence on the web

paper_content:

The Web has acquired immense value as an active, evolving repository of knowledge. It is now entering a new era, which has been called “Web 2.0”. One of the essential elements of Web 2.0 is harnessing the collective intelligence of Web users. Large groups of people are remarkably intelligent, and are often smarter than the smartest people in them. Knowledge as collective intelligence is socially constructed from the common understandings of people. It works as a filter for selecting highly regarded information with collective annotation based on bottom-up consensus and the unifying force of Web-supported social networks. The rising interest in harnessing the collective intelligence of Web users entails changes in managing the knowledge of individual users. In this paper, we introduce a concept of knowledge management based on harnessing the collective intelligence of Web users, and explore the technical issues involved in implementing it.
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paper_title: Holistic Sense Making : Conflicting Opinions , Creative Ideas , and Collective Intelligence

paper_content:

Purpose – The purpose of this work is to introduce a generic conceptual and methodological framework for the study of emergent social and intellectual patterns and trends in a diverse range of sense‐and decision‐making activities.Design/methodology/approach – The development of the framework is driven by three motivating challenges: capturing the collective intelligence of science, fostering scientific discoveries in science and e‐Science, and facilitating evidence‐based librarianship (EBL). The framework is built on concepts such as structural holes and intellectual turning points, methodologies and techniques for progressive knowledge domain visualization and differentiation of conflicting opinions, and information integration models to achieve coherent transitions between different conceptual scales.Findings – Structural holes and turning points are detected and validated with the domain of terrorism research as an example. Conflicting opinions are differentiated in the form of a decision tree of phras...
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paper_title: Self-Organization in Biological Systems

paper_content:

From the Publisher: ::: "Broad in scope, thorough yet accessible, this book is a self-contained introduction to self-organization and complexity in biology - a field of study at the forefront of life sciences research."--BOOK JACKET.
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paper_title: Toward collective intelligence of online communities: A primitive conceptual model

paper_content:

Inspired by the ideas of Swarm Intelligence and the “global brain”, a concept of “community intelligence” is suggested in the present paper, reflecting that some “intelligent” features may emerge in a Web-mediated online community from interactions and knowledge-transmissions between the community members. This possible research field of community intelligence is then examined under the backgrounds of “community” and “intelligence” researches. Furthermore, a conceptual model of community intelligence is developed from two views. From the structural view, the community intelligent system is modeled as a knowledge supernetwork that is comprised of triple interwoven networks of the media network, the human network, and the knowledge network. Furthermore, based on a dyad of knowledge in two forms of “knowing” and “knoware”, the dynamic view describes the basic mechanics of the formation and evolution of “community intelligence”. A few relevant research issues are shortly discussed on the basis of the proposed conceptual model.
---
paper_title: From social computing to reflexive collective intelligence: The IEML research program

paper_content:

The IEML research program promotes a radical innovation in the notation and processing of semantics. IEML (Information Economy MetaLanguage) is a regular language that provides new methods for semantic interoperability, semantic navigation, collective categorization and self-referential collective intelligence. This research program is compatible with the major standards of the Web of data and is in tune with the current trends in social computing. The paper explains the philosophical relevance of this new language, expounds its syntactic and semantic structures and ponders its possible implications for the growth of collective intelligence in cyberspace.
---
paper_title: On model design for simulation of collective intelligence

paper_content:

The study of collective intelligence (CI) systems is increasingly gaining interest in a variety of research and application domains. Those domains range from existing research areas such as computer networks and collective robotics to upcoming areas of agent-based and insect-based computing; also including applications on the internet and in games and movies. CI systems are complex by nature and (1) are effectively adaptive in uncertain and unknown environments, (2) can organise themselves autonomously, and (3) exhibit 'emergent' behaviour. Among others, multi-agent systems, complex adaptive systems, swarm intelligence and self-organising systems are considered to be such systems. The explosive wild growth of research studies of CI systems has not yet led to a systematic approach for model design of these kinds of systems. Although there have been recent efforts on the issue of system design (the complete design trajectory from identifying system requirements up to implementation), the problem of choosing and specifying a good model of a CI system is often done implicitly and sometimes even completely ignored. The aim of this article is to bring to the attention that model design is an essential as well as an integral part of system design. We present a constructive approach to systematically design, build and test models of CI systems. Because simulation is often used as a way to research CI systems, we particularly focus on models that can be used for simulation. Additionally, we show that it is not necessary to re-invent the wheel: here, we show how existing models and algorithms can be used for CI model design. The approach is illustrated by means of two example studies on a (semi-automated) multi-player game and collaborative robotics.
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paper_title: Swarm Intelligent Surfing in the Web

paper_content:

Traditional ranking models used in Web search engines rely on a static snapshot of the Web graph, basically the link structure of the Web documents. However, visitors' browsing activities indicate the importance of a document. In the traditional static models, the information on document importance conveyed by interactive browsing is neglected. The nowadays Web server/surfer model lacks the ability to take advantage of user interaction for document ranking. We enhance the ordinary Web server/surfer model with a mechanism inspired by swarm intelligence to make it possible for the Web servers to interact with Web surfers and thus obtain a proper local ranking of Web documents. The proof-of-concept implementation of our idea demonstrates the potential of our model. The mechanism can be used directly in deployed Web servers which enable on-the-fly creation of rankings for Web documents local to a Web site. The local rankings can also be used as input for the generation of global Web rankings in a decentralized way.
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paper_title: Termites as models of swarm cognition

paper_content:

Eusociality has evolved independently at least twice among the insects: among the Hymenoptera (ants and bees), and earlier among the Isoptera (termites). Studies of swarm intelligence, and by inference, swarm cognition, have focused largely on the bees and ants, while the termites have been relatively neglected. Yet, termites are among the world’s premier animal architects, and this betokens a sophisticated swarm intelligence capability. In this article, I review new findings on the workings of the mound of Macrotermes which clarify how these remarkable structures work, and how they come to be built. Swarm cognition in these termites is in the form of “extended” cognition, whereby the swarm’s cognitive abilities arise both from interaction amongst the individual agents within a swarm, and from the interaction of the swarm with the environment, mediated by the mound’s dynamic architecture. The latter provides large scale “cognitive maps” which enable termite swarms to assess the functional state of their structure and to guide repair efforts where necessary. The crucial role of the built environment in termite swarm cognition also points to certain “swarm cognitive disorders”, where swarms can be pushed into anomalous activities by manipulating crucial structural and functional attributes of the termite system of “extended cognition.”
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paper_title: Group decision making in swarms of honey bees

paper_content:

This study renews the analysis of honey bee swarms as decision-making units. We repeated Lindauer's observations of swarms choosing future home sites but used modern videorecording and bee-labelling techniques to produce a finer-grained description of the decision-making process than was possible 40 years ago. Our results both confirm Lindauer's findings and reveal several new features of the decision-making process. Viewing the process at the group level, we found: (1) the scout bees in a swarm find potential nest sites in all directions and at distances of up to several kilometers; (2) initially, the scouts advertise a dozen or more sites with their dances on the swarm, but eventually they advertise just one site; (3) within about an hour of the appearance of unanimity among the dancers, the swarm lifts off to fly to the chosen site; (4) there is a crescendo of dancing just before liftoff, and (5) the chosen site is not necessarily the one that is first advertised on the swarm. Viewing the process at the individual level, we found: (1) the dances of individual scout bees tend to taper off and eventually cease, so that many dancers drop out each day; (2) some scout bees switch their allegiance from one site to another, and (3) the principal means of consensus building among the dancing bees is for bees that dance initially for a non-chosen site to cease their dancing altogether, not to switch their dancing to the chosen site. We hypothesize that scout bees are programmed to gradually quit dancing and that this reduces the possibility of the decision-making process coming to a standstill with groups of unyielding dancers deadlocked over two or more sites. We point out that a swarm's overall strategy of decision making is a “weighted additive strategy.” This strategy is the most accurate but also the most demanding in terms of information processing, because it takes account of all of the information relevant to a decision problem. Despite being composed of small-brained bees, swarms are able to use the weighted additive strategy by distributing among many bees both the task of evaluating the alternative sites and the task of identifying the best of these sites.
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paper_title: Holistic Sense Making : Conflicting Opinions , Creative Ideas , and Collective Intelligence

paper_content:

Purpose – The purpose of this work is to introduce a generic conceptual and methodological framework for the study of emergent social and intellectual patterns and trends in a diverse range of sense‐and decision‐making activities.Design/methodology/approach – The development of the framework is driven by three motivating challenges: capturing the collective intelligence of science, fostering scientific discoveries in science and e‐Science, and facilitating evidence‐based librarianship (EBL). The framework is built on concepts such as structural holes and intellectual turning points, methodologies and techniques for progressive knowledge domain visualization and differentiation of conflicting opinions, and information integration models to achieve coherent transitions between different conceptual scales.Findings – Structural holes and turning points are detected and validated with the domain of terrorism research as an example. Conflicting opinions are differentiated in the form of a decision tree of phras...
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paper_title: CorpWiki: A self-regulating wiki to promote corporate collective intelligence through expert peer matching

paper_content:

One of the main challenges that organizations face nowadays, is the efficient use of individual employee intelligence, through machine-facilitated understanding of the collected corporate knowledge, to develop their collective intelligence. Web 2.0 technologies, like wikis, can be used to address the above issue. Nevertheless, their application in corporate environments is limited, mainly due to their inability to ensure knowledge creation and assessment in a timely and reliable manner. In this study we propose CorpWiki, a self-regulating wiki system for effective acquisition of high-quality knowledge content. Inserted articles undergo a quality assessment control by a large number of corporate peer employees. In case the quality is inadequate, CorpWiki uses a novel expert peer matching algorithm (EPM), based on feed-forward neural networks, that searches the human network of the organization to select the most appropriate peer employee who will improve the quality of the article. Performance evaluation results, obtained through simulation modeling, indicate that CorpWiki improves the final quality levels of the inserted articles as well as the time and effort required to reach them. The proposed system, combining machine-learning intelligence with the individual intelligence of peer employees, aims to create new inferences regarding corporate issues, thus promoting the collective organizational intelligence.
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paper_title: Decisions 2.0: the power of collective intelligence

paper_content:

Information markets, wikis and other applications that tap into the collective intelligence of groups have recently generated tremendous interest. But what�s the reality behind the hype?
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paper_title: Regional intelligence: distributed localised information systems for innovation and development

paper_content:

Technological information is recognised as an important factor shaping regional systems of innovation and innovative regions. However, little has been written on how regions set up and manage this vital resource. This paper focuses on regional intelligence: distributed information systems localised over a region allowing continuous update and learning on technologies, competitors, markets, and the environment. We start by defining regional intelligence with respect to the concepts of business intelligence, organisational, and collective intelligence. We look at a number of case studies and experiences gained in the context of EU regional innovation and regional economic strategies, which highlight early forms of regional intelligence. We examine the fundamental information modules making up regional intelligence, including, R&D dissemination, technology and market watch, company benchmarking and competition analysis, regional foresight, and regional performance. We discuss the integration of distributed information systems and solutions which may be given to consolidate public content applications with the internal information systems of companies, and the role of information integration in the continuous making and remaking of innovative regions.
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paper_title: Collective Intelligence and its Implementation on the Web: algorithms to develop a collective mental map

paper_content:

Collective intelligence is defined as the ability of a group to solve more problems than its individual members. It is argued that the obstacles created by individual cognitive limits and the difficulty of coordination can be overcome by using a collective mental map (CMM). A CMM is defined as an external memory with shared read/write access, that represents problem states, actions and preferences for actions. It can be formalized as a weighted, directed graph. The creation of a network of pheromone trails by ant colonies points us to some basic mechanisms of CMM development: averaging of individual preferences, amplification of weak links by positive feedback, and integration of specialised subnetworks through division of labor. Similar mechanisms can be used to transform the World-Wide Web into a CMM, by supplementing it with weighted links. Two types of algorithms are explored: 1) the co-occurrence of links in web pages or user selections can be used to compute a matrix of link strengths, thus generalizing the technique of &201C;collaborative filtering&201D;; 2) learning web rules extract information from a user&2018;s sequential path through the web in order to change link strengths and create new links. The resulting weighted web can be used to facilitate problem-solving by suggesting related links to the user, or, more powerfully, by supporting a software agent that discovers relevant documents through spreading activation.
---
paper_title: Swarm intelligence in animals and humans.

paper_content:

Electronic media have unlocked a hitherto largely untapped potential for swarm intelligence (SI; generally, the realisation that group living can facilitate solving cognitive problems that go beyond the capacity of single animals) in humans with relevance for areas such as company management, prediction of elections, product development and the entertainment industry. SI is a rapidly developing topic that has become a hotbed for both innovative research and wild speculation. Here, we tie together approaches from seemingly disparate areas by means of a general definition of SI to unite SI work on both animal and human groups. Furthermore, we identify criteria that are important for SI to operate and propose areas in which further progress with SI research can be made.
---
paper_title: The Allocation of Collaborative Efforts in Open-Source Software

paper_content:

The article investigates the allocation of collaborative efforts among core developers (maintainers) of open-source software by analyzing on-line development traces (logs) for a set of 10 large projects. Specifically, we investigate whether the division of labor within open-source projects is influenced by characteristics of software code. We suggest that the collaboration among maintainers tends to be influenced by different measures of code complexity. We interpret these findings by providing preliminary evidence that the organization of open-source software development would self-adapt to characteristics of the code base, in a [`]stigmergic' manner.
---
paper_title: Toward collective intelligence of online communities: A primitive conceptual model

paper_content:

Inspired by the ideas of Swarm Intelligence and the “global brain”, a concept of “community intelligence” is suggested in the present paper, reflecting that some “intelligent” features may emerge in a Web-mediated online community from interactions and knowledge-transmissions between the community members. This possible research field of community intelligence is then examined under the backgrounds of “community” and “intelligence” researches. Furthermore, a conceptual model of community intelligence is developed from two views. From the structural view, the community intelligent system is modeled as a knowledge supernetwork that is comprised of triple interwoven networks of the media network, the human network, and the knowledge network. Furthermore, based on a dyad of knowledge in two forms of “knowing” and “knoware”, the dynamic view describes the basic mechanics of the formation and evolution of “community intelligence”. A few relevant research issues are shortly discussed on the basis of the proposed conceptual model.
---
paper_title: On model design for simulation of collective intelligence

paper_content:

The study of collective intelligence (CI) systems is increasingly gaining interest in a variety of research and application domains. Those domains range from existing research areas such as computer networks and collective robotics to upcoming areas of agent-based and insect-based computing; also including applications on the internet and in games and movies. CI systems are complex by nature and (1) are effectively adaptive in uncertain and unknown environments, (2) can organise themselves autonomously, and (3) exhibit 'emergent' behaviour. Among others, multi-agent systems, complex adaptive systems, swarm intelligence and self-organising systems are considered to be such systems. The explosive wild growth of research studies of CI systems has not yet led to a systematic approach for model design of these kinds of systems. Although there have been recent efforts on the issue of system design (the complete design trajectory from identifying system requirements up to implementation), the problem of choosing and specifying a good model of a CI system is often done implicitly and sometimes even completely ignored. The aim of this article is to bring to the attention that model design is an essential as well as an integral part of system design. We present a constructive approach to systematically design, build and test models of CI systems. Because simulation is often used as a way to research CI systems, we particularly focus on models that can be used for simulation. Additionally, we show that it is not necessary to re-invent the wheel: here, we show how existing models and algorithms can be used for CI model design. The approach is illustrated by means of two example studies on a (semi-automated) multi-player game and collaborative robotics.
---
paper_title: Group performance and decision making.

paper_content:

Theory and research on small group performance and decision making is reviewed. Recent trends in group performance research have found that process gains as well as losses are possible, and both are frequently explained by situational and procedural contexts that differentially affect motivation and resource coordination. Research has continued on classic topics (e.g., brainstorming, group goal setting, stress, and group performance) and relatively new areas (e.g., collective induction). Group decision making research has focused on preference combination for continuous response distributions and group information processing. New approaches (e.g., group-level signal detection) and traditional topics (e.g., groupthink) are discussed. New directions, such as nonlinear dynamic systems, evolutionary adaptation, and technological advances, should keep small group research vigorous well into the future.
---
paper_title: Decisions 2.0: the power of collective intelligence

paper_content:

Information markets, wikis and other applications that tap into the collective intelligence of groups have recently generated tremendous interest. But what�s the reality behind the hype?
---

Title: Collective Intelligence in Humans: A Literature Review
Section 1: INTRODUCTION
Description 1: Introduce the study of collective intelligence in humans, define terminology, and set the scope and objectives of the review.

Section 2: METHODS
Description 2: Explain the approach taken for literature selection, keyword search criteria, and the process of analyzing the selected literature.

Section 3: RESULTS
Description 3: Present the identified pattern in the literature and discuss the three levels of abstraction: micro-level, macro-level, and the level of emergence.

Section 4: The micro-level: Enabling factors of human beings
Description 4: Discuss collective intelligence at the micro-level, focusing on psychological, cognitive, and behavioral elements that enable collective intelligence.

Section 5: The macro-level: Output of the System
Description 5: Explain collective intelligence at the macro-level, particularly in the context of the "wisdom of crowds" effect and the impact of diversity, independence, and aggregation.

Section 6: The Level of Emergence: From Local Interactions to Global Patterns
Description 6: Explore how macro-level behavior emerges from micro-level interactions, using theories of complex adaptive systems, self-organization, and emergence.

Section 7: DISCUSSION AND CONCLUSIONS
Description 7: Summarize the review findings, propose a conceptual framework for studying collective intelligence, and suggest directions for future research.