So, welcome to this presentation on transforming interactions between government and communities through the use of social media. I'm Dr. Pat Franks, and I do lead a research project through InterPARES Trust that studies social media and trust in government. And Lacey Ryan Banks, we'll call her Ryan, is a graduate research assistant working on the project with me. And she's doing some work on specific cities, local governments. So, she's going to be giving you some real world examples of what we're looking at here. And this is only a piece of the project. When I get to another point, I'll explain to you how one of the other instructors here at San Jose is involved and where. So, our talking points are just really three. What it means to trust, social media and power and identity, the relationships and local government and social media. And then it'll be summarized in just a few key points. So, what is trust? According to InterPARES Trust, the research agenda that we're following, there is a terminology database. Trust is the faith or belief in a person or a thing with confidence of some action or the expectation of the safety of the thing. So, really what we're saying is I believe you're going to do what I expect that you will do, right? And that it will be good for me. So, that's what trust is here. Trust is associated with an agent is in a financial trust or some type of trustworthy system. And then we get into a term there called trustworthiness, where we're looking at the accuracy, the reliability, the authenticity of a record. So, there are a lot of ways to look at a definition of trust. But the way I'm using it here and the way we're using it in our study is I believe you're going to do something that is going to be good for me, my benefit. So then, what is trust in government? Well, according to Levi and Stoker, trust in government is an evaluation of whether or not political authorities and institutions are performing in accordance with normative expectations held by the public. So, if we take a look at this slide, you'll see that the first principle in the code for federal employees. Starts with the statement, public service is a public trust. And if you were trying to determine trust in government, you might ask a research question like, do you have confidence in the local or federal or state government to do what is right? And then you would provide some type of a like or stale that they could respond to perhaps saying never some of the time, about half of the time. Most of the time are almost always, definitely not almost always right now. As you can see on this slide, perceptions of trust in government according to the Pew Research Institute is at an all-time low. It went from 73% in the Johnson administration. That was right after the Kennedy years when there was a lot of enthusiasm. And even though there was that horrible event and President Kennedy lost his life, there was still this feeling that we could do almost anything. So, trust was pretty high at 73%, but it fell dramatically. And there were a lot of events, of course, that occurred of Vietnam War, for example. But where we are now, you see on this, is like 19%. And this is perception of trust in the government. And this was the end of 2013. It may even be lower now if you've been watching the news or checking into your social media accounts. Perception of trust in government in Canada is a little bit better. This was measured by an ECOS Research Associates. And the question that was asked here is, how much do you trust the government in Ottawa or Washington? Because they did also ask the US citizens to do what is right. And if we wanted a one-sentence summary of what the polls told us about Canadian democracy in 2013, it's reported that the statement would be, we're losing faith. And I would say that, of course, it's the same thing in the United States. Now, there are some countries worldwide that are not experiencing this decline, this dramatic decline in trust. But our two countries certainly are. Now, when we're looking at trust and we're trying to tie it to social media, what we're looking at is social media is a source of information. And so the second thing we're trying to determine is, so really, what source of information do you go to? In order to get the breaking news, to get your regular news, to check up on what you've heard, if you want to confirm something that you've heard that should be in the news. And in this case, there's a formula for trust, which means that you've got authority and helpfulness and intimacy. Those are all the good things. But that's divided by self-promotion. I see this self-promotion happening a lot on mayoral sites. And I was just noticing it today, the mayor of New York City not standing or supporting the police department. Not that I think he should have, but I've noticed this on many other sites that we visited. One department may be down as far as citizen trust. Well, another one is higher, and it's usually when they are agreeing or servicing, providing good service to the community. So it's kind of a very complicated situation to be able to understand. But the important thing here is that social media now is at a 47% trust level. That means that 47% of the people would look to social media and believe what they say as far as is included in the social media. So they'd look at Twitter and say, I do believe that that's correct, or I do believe what I'm reading on Facebook and so on. Traditional media is at 65%, but you'll see that online search engines now is equal. So what we're learning from there then, if you wanted to apply it to your own organizations, is that traditional media is expensive, and it may not be something that you need to use in order to reach your patrons, your customers, your citizens. Because the same number would be able to find that information on the website, and it would cost the organization that's trying to get that message out a lot less. This is very important, of course, for local, state, federal government. So social media, trust in social media is rising. It's been rising over the last few years. Trust in traditional media has been declining. Now, when we look at both trust in government and trust in social media, trying to see if there's some kind of a relationship, if we do a better job at social media, will that increase trust? We look to what the government is doing now, and if you have engaged with your government electronically, perhaps paying your taxes or voting or purchasing something, I know I pay for my driver's license that way. This is all e-government. The government is using the technology, but it's to support government operations, to engage citizens, to provide services. But it's kind of that one-way street. You are in there. You are performing some actions. You're entering into transaction, but it really isn't there to get you to collaborate with government. What it's there for is to provide you with a service. That service should actually be cheaper for the local government, state government, federal government to provide because they're using technology. But what we're interested in is how can we go beyond just if you were a government organization, how could you go beyond e-government into the e-governance? The e-governance is a little different. This is where citizens should be able to cooperate, collaborate, communicate with the government and to actually make changes in the way the government operates. And we're seeing a lot of that now if you've been watching TV with the protests. It's one way for individuals to attempt to make a change in a system that they believe needs change. What we're looking at is how can social media be a part of it? Is social media a part of this now? So when President Obama came into office in 2009, he declared that he wanted an open and transparent government. And he told his agencies that they should start using social media in order to share information with the citizens. So that was the beginning of in the United States openness and transparency on part of the government, at least as a philosophy. So social media was used. And if it's used correctly, public trust should be increased. If it's not perceived as being used correctly, if it's just being used as a media campaign, for example, to try to tell someone this is correct when it's not, it's not going to work. And I've got a couple of examples of that for you too. But what we're believing, what we believe in our research here is that openness and trust through the use of social media can increase public trust. And if you follow that arrow across, if public trust is increased, then social capital, social capital is the feeling that an individual's interests are met.  Well, then your individual interest has been met, and so you feel really good about that. So there's good feeling there that can equate to better thought about your government and then better cooperation on your side. Maybe you'll vote to increase taxes next time so they could get a new truck to do filling these potholes. But also to share an interest and then to common interests where you have groups that are actually working together to do something. So public trust, though, can also be decreased depending on how social media may be used. As I said, I'll show you an example of that. But in any case, whether for good or for ill, policymaking can be affected. That's what we're trying to look at. We're trying to study how this will happen and for public administrators eventually to come up with guidelines that will help them understand how to use this in a good way to increase this involvement, this interaction with their citizens so that everybody can have their needs met. Now the next part of this is about social media and power and identity. And we actually have some impressions of the government already, right? How many of you have seen this before or heard it? I'm from the government. I'm here to help, right? And you roll your eyes sometimes when you hear that. But that's a cliche. But there are some and I'm using the police department only because my father was part-time police officer. Oh my gosh, in a very small town. And so I have a fondness for visiting police departments, but I'm not always saying they're right. So, but in this case, I found this one and Brimfield, Ohio is a town of 10,000 people. And yet back in 2013, they had 88,000 Facebook likes.  And it's of course not all because they were doing social media and they were doing it right. It's also because that police department was doing something right. And then they used social media as a means of communication to let the community know what they were doing, what they can do, what kind of services they can provide and to listen when the citizens engage with them in Facebook and social media. In order to get that reciprocal agreement going, although of course not a signed contract, but this understanding that this trust that the police department in this case would do what's right for the citizen that was asking for assistance. Now in this case, of course, it's one of these pictures where the police department helps unfortunate disadvantaged youth go shopping, get ready for school that type of thing. So that's always a good thing. Remember that number, 88,000. All right. Grimfield police use all kinds of devices. They make sure that their social media can be adapted to mobile devices. They use Facebook and they use Twitter really beautifully. And they do have the app that you can download so that you can follow them. And if you would look on this slide, what you can see is by now they're up to something 146,359 likes. Now that I think was in the spring. So that was maybe nine months or so after the 88,000. They've moved up to 146. The only city that has more interaction on Facebook than they do with citizens is New York City. New York City is so much larger. Remember, there's only 10,000 citizens in this town. So on their site, I went to look to see what they were doing right. You know, why do people keep coming back? And I saw this picture of the dog the first time I visited. I was really sad because I didn't know why that dog was behind the chain link fence. But as I read, of course, I found out the police chief found him in the morning. And he says, please help us with this young puppy wants to find his way home. And so they put out a call and they put out the picture. And they've got that little guy there that they're taking care of for a citizen who has lost that puppy to be able to come and get it. So not like in a cattle or something when they're picked up and nobody knows where they are here using social media to let people know. So what I got out of this right down below where it says involved is somebody saw this and said whatever happened to the Golden Retriever. So apparently they've done this before and also appreciated right before that is, you know, this is really awesome that you do that. So you're seeing there's a service for someone. Others appreciate that and know that if their animal happened to be loose and was picked up. I'm going to dog catch her in this case, though, the police, they would be notified through social media on the right hand side. This was from today. This town is not unaffected by the events that are going on from Ferguson and from now New York City. So the dialogue is about police wearing cameras. And this is a picture of a policeman wearing a camera. And I didn't read the article underneath, but what interested me was one of the tweets way down at the or I should say post down at the bottom kind of fell in with my interest in social media. It's about keeping track of it, right? And somebody says, you know, this is another concern that we're not even talking about if you do wear these cameras then. How do you retain them? Because you do have a data retention rules that have to be followed. And also freedom of information request. There's a freedom of information act. So these cameras then would videotape that tape. Can you tell? I'm old videotape. They would record. The digital information would be recorded on servers. You would have to have rules now as to how long you would keep that before you would reuse wherever they happen to be stored or before you would destroy them. You'd have to make sure they were available for individuals that want them through freedom of information and are entitled to them. And then you have to build on the cost because all of this costs something. So police department budget is going to be affected as well. So anything that we're talking about really affects the entire organization. Now this for my town before I leave it, at Brimfield, December 3rd, that's today. They're now up to 174,991 likes. And I would just say visit it. You want to see what people are saying even from other communities that don't live in this town, that they get services met too. And that they just really appreciate everything that's being done. However, there's another side to this too. Our poor eagle is saying really now I've given you all the good news. You still trust the government. Does everybody really trust the government? Well, if you ask the Native Americans, they might say, oh, not really. Look what happened to us, right? So now we have the really sad side of this. We have the Ferguson department, the pictures were taken. And what happens today is that you can't erase what's out there. We can say for retention, disposition, our organization can remove whatever responsible for. But somebody else has the picture somewhere.  And when we talk about trust in police or trust in mayor or trust in city council, images are so powerful. In this case here, not only images, but we have someone who used his Facebook account to threaten the police officer in this case.  But if we're unable to locate him, then let's shoot the wife and the children. And so we see the anger and frustration being built and mounted. And the police, again, trying to keep some kind of order if possible. And then you have all kinds of people just chiming in on their own Twitter feeds. This is one. And this is where Charles Barkley, you know, basketball player, right, said that maybe profiling is wrong, but maybe sometimes it's not. So he was trying to get into a conversation, a dialogue, which didn't go well because then people were upset with him on social media. So his last tweet or not tweet, his last statement today to the press was I'll never do social media. I don't want to talk to those idiots. So here we're getting someone very upset with being, I guess, bullied for his comments on social media. Now, I know this is a lot of information that are just examples. But I think what you're seeing is the contrast between services that are assisting the citizens, the way that Brimfield used social media in order to get people to cooperate and to collaborate and to appreciate what they're doing. And then on the other side of it, how it can be used in order to, I think, make things worse sometimes. Now, some of this information, if you were looking at it, you'd say, why do they keep that up on their site anyway? Because people are there and they're upset and they're posting things that maybe would incite others. But really, if you're an elected official, you've got to be careful even about removing things. This example I thought was really, really directed to the point. It was Indiana Governor Mike Pence. And when we talk about trust, this was broken trust. He really didn't even do anything wrong. Somebody who worked for him did, but he was the one who felt the brunt of it. He had an idea about how the Supreme Court should rule on a case before it. And what he did was express his personal opinion, which he might not have done if he had thought about it a little bit in advance. When he expressed that opinion, the citizens that were following him were very upset. And within 24 hours, there were 1,000 comments, and not many of them were in his favor. And so somebody on his staff decided to delete the comments. And that was not a good thing. Because what quickly came up was another Facebook page, and it was called Spencer Ship. And the people who started that Facebook page invited everybody else that had their comments deleted from his real Facebook page to post again. And they did. So the resentment had mounted not only did they disagree with what he said in the first place, but then by removing all of their comments, they disagreed with that action. Unfortunately, the governor then he did apologize, but he came out and he said, we need a new improved policy on Facebook. So remember my circle where I'm saying feedback will then impact the policymaking. The only problem in this case is I read the policy and the policy was clear they should not have been removed. So it wasn't that what it should have been if this really was a new person that didn't know it really should have been training. So that's what was lacking in this case. Briefly, I wanted to show that we in the United States and Canada are not the only countries that are dealing with social media. Social media in the Arab world is influencing societal and cultural changes as well. And you can see here that social media is empowering people in these countries in order to understand where they fit in. And it does influence change in their community.  And it's empowering Arab women, for example. So it's quite powerful if used properly. Additional questions related to an individual's sense of identity. Remember I said, you know, you identify that's what we saw with the people on one side or other side of any kind of controversy or issue is that they're identifying with that. In this case, people are learning in Lebanon and Egypt, for example, that use of social media increases their national identity. But in other cases, it increases their identity as a citizen of the globe, not just of their own country. And you see that United Arab Emirates and in Jordan. And then in some cases, it does enforce their regional identity, but even the religious identity, which I found surprising. I mentioned that I did have just a couple of just that line. I had a couple of sites here that affected this. And again, if you trust that what you see in social media is correct, then you would say these are correct. If you did not, of course you would say this must be made up by someone. And that's something that we have to be very careful with to are these official sites that we're looking at? Or are they sites that were made by someone else to look as if they were official? So even the United States government has a site that helps you identify which are official sites. Otherwise, you could be fooled. But in this case, this is an extreme where the founder of Russia's Facebook, and it really isn't Facebook. What is it called? It's a book. I'm not sure I'm saying it right, Svetlana. So maybe you know and I don't. But what they're saying here is that the government took over their social media. Go ahead, Svetlana. Do you know something about this? Yeah, I heard about it. Yeah, that he was kind of forced to give control. Not mostly for content, but mostly for people who post, who make posts. And then the special services can show away and attract the people who make some posts. So you're saying this really wasn't to control content? The way the headline is written is not correct? Yeah, I think so. Okay, yeah. And it's very difficult for those of us who are seeing these messages to understand what is true and what is not, even with what we see here. I see on the right-hand side, this was someone who was trying to get out a different message. This came from the Ukraine. And what they were trying to do is get out information about some people, I think, who were killed. Oh, I don't have that back there. What I wanted to end with though on this one was that I believe the site is up and being run independently now because I went back to it and it looks fine. And you could get in and become a member of it. So it doesn't seem as if it were censored as I thought it might have been. And I just tried that today. So I found this very interesting that we could get information through social media. Other countries have their own kinds of tools that they use. And other ways of, I think, either monitoring it or being able to use it to provide information. And I would like to say influence and not control. I spoke with someone from China and we were joking about social media. And she said, you know, you notice I don't categorize any of this. I said, why not? Because she said here in China, everything is under control. So she was kind of taking the other stance that in their country it's very much out of their ability to be free with what they want to communicate. I don't know. But what is interesting about the Interparez Trust research project that I'm on is that this is not my problem because we have people from the Ukraine and Russia both looking at these issues, social media from their own perspective. So we will get the perspective from the people in those countries. We have researchers all throughout Europe, South America, Asia and it's just unbelievable. So we can't wait to share information once we're all done with this. But now I want to turn this over to Ryan because she's going to talk to you about what we specifically are interested in. This is the part we're working on. It's local government social media. So Ryan, you take it away. Okay. If I could just have moderator privileges. Oh, you did. Yes. And I have to give it back to you because you went out. So I will do that right now. Thank you. So as we see here, there are 20 cities that we have decided to look at. 10 Canadian, 10 American. When I came on to this study, they've been working for a year. So all these cities are already picked. And when you came in, as you see, there's the list of the US cities. They're pretty fairly diverse. Of course, New York's the biggest one out of all of them, but they range. Most of them, I would say are mid-sized cities or excuse me, the most part. Yeah, most of them have at least 300,000 people with Riverside being the smallest. So fairly large cities, at least on the US side. I don't remember the data for the Canadian, but I would guess they're probably very similar. So one of the cities that I've been looking at is Raleigh. Raleigh is one of the major cities in North Carolina going to our next slide. We can see that it was founded in 1792. They are very big on banking and finance there, in addition to them being part of the research triangle, which includes Raleigh, Durham, and Chapel Hill. They're social media. Well, for their e-government, they've placed 10th in the 2013 Digital Cities Survey. And this year, they were a finalist for Best of the Web City Portal category.  There doesn't seem to be a lot of data provided. However, they are very good about providing links to all of their online services. So for the most part, Raleigh seems to use social media to inform their citizens about the programs and services and events and stuff that they're doing. And they like to also promote things like their recreation and their parks and other stuff that will actually go over later. But as we can see from this page, this is what their social media page looks like. They actually do keep it fairly updated. As you can see, it was just last updated on October 30th. And from there, you can access all of the major city portals. So their Facebook page and whatnot. And at count in September, they had, let's see, 2,585 Facebook likes. So not a whole lot. Not a lot better with Twitter followers where they had 16,800. And then their mayor had like 1,500. So as you can see, City Portal is definitely what is used the most out of all of that. This is the main thing that we've been working on lately. One of the other researchers, in fact, I believe she is a professor for San Jose. She took all the data that was gathered from Twitter and analyzed it. She found out how many tweets they did. And then she ran a program to see what was positive versus what was negative. For most of the cities, positive, neutral, I'm sorry, was the most common category. So they didn't really say anything that was perceived as good or bad. For Raleigh, they're actually a really positive neutral city. They had one of the smallest negative analysis from the column there. There's ended up being an average of 4.9. And so it was just, that's actually pretty impressive, considering all the things that can go wrong for a city. And as you can see, their tweets tended to stay fairly consistent, though I noticed there was a change in May and August. I should go back and say what I have been doing is going through this analysis and finding out what was going on to cause these, we'll call them wild variations, though they're not very wild. But starting in February of this year, they got, they started going over 400, almost consistently except for whatever happened in June. August 2013 was the highest number of negatives for the city. And there's a very good reason for that. They enacted a law about not ceding the homeless. And as we've seen in Florida, people are not happy about that. Well, same thing happened in Raleigh. People were tweeting all the time about why would they enact this law. It was kind of crazy to them. Like, why would you charge $800 a day for permit to feed the homeless? People were very unhappy about that. They were also, something was also going on with trash collection and road work. That month, don't know what happened quickly, but yeah. And then in September actually turned around and became their month with the most neutral statements. And then going on, February had the most positive statements. And from what I was able to gather for that, a lot of it had to do with publics was coming in and building a new complex. So that also, they were also talking about other business and development conversion projects. And of course they got hit with what we like to term here as snowpocalypse. They got hit with the second part of that. And people were really impressed with their responses that they were putting out. So they were telling people about road closures and school closures. And they were staying really, really on top of telling people about the winter weather problems that were going on, which in getting what happened in Atlanta right before then, I think people really appreciated that. And another major thing that they were talking about was the fact that Google Fiber might be coming into town. And for anyone who lives in a major city, we're all waiting for this. So a lot of it was talking about how much better Google Fiber will be than Time Warner. So that's basically what is going on with the statistical analysis. It's just going through seeing what happens, where, why, and how that translates into citizens engaging with their government. So I'm going to give it back to Dr. Franks to talk about our key points. Thank you, Ryan. And I didn't intend to say this, but you had mentioned the snowpocalypse. And one of the events this fall was snow in Buffalo area. Here in the Northeast, we sit pretty hard. And just as you mentioned for Raleigh, the areas up here in Minneapolis too are using mobile apps for citizens to be able to report needs. So during times of a disaster like this, which can really be a disaster when you have so much snow all at once, but they're also being connected with the Internet of Things. So there's a lot of requesting, for example, plowing in certain areas. And the messages are, they're using GIS and they're actually sending transmission right through the government without having to call, without having to worry about anything. And they're mapping the locations of where all their trucks are so that they could better move them when they need them. And what they're saying is that there's a lot of interactivity with the citizens, and the citizens are benefiting from the investment in technology that the government has made. So those are the good things that you see that do increase the public trust, public attitude toward the government and they see that they can trust their government in times of emergency to be able to handle things in a way that is good for them. But as Ryan said, we have some key points and then we have time for questions and answers. Mainly what we're taking away from our study, and Ryan did just one of 20 cities. And in each city, we did not only their Twitter account and the Twitter accounts for the police chief, the mayor and the clerk, but we also did take a look at Facebook pages. We looked at all of the social media they were using. We looked at and are still looking at the policies. We're looking at the way they are maintaining records, whether or not they consider social media records that have to be maintained, if so, how they're doing, capturing them and retaining them. And what we're hoping to do at the end of this is identify two cities that are outstanding as far as service positive effects on the citizens in Canada and in the U.S. and to glean from that tips that we can then share with other public administrators so that they can understand how to use social media more effectively to be able to engage with their citizens in a positive manner. So it's been really interesting. So what we're saying is social media then is increasingly used by government to inform, interact with and influence citizens. And it's also being increasingly used by citizens so to inform, interact with and influence their government. So there's that mutual tension there. And the use of social media, the way we're using it now, think about the history books and think about the artifacts that we have from the past, you know, and the way we look at history and try to find out what happened before us. What we have is social media as artifacts or we will have them if we can retain them. And what we're seeing now being played out in Facebook and in Twitter and LinkedIn and all of these other social media, your Pinterest pictures there. This will be our history. This will be a record of what life was like at this time if we can find a way to preserve it. So this social media will have an impact on memories and identities and on our communities. So the research agenda again that we're involved in really wants to take a look at local, national, international networks of policies, procedures, regulations, standards and legislation concerning digital records that are entrusted to the internet. So not just the social media. We're looking at all kinds of digital information. And what we're trying to do is ensure that public trust can be grounded on evidence of good governance. We're trying to find a way to make it right where there are problems and that this will create for us, if we can do this right, a persistent digital memory so that we don't lose our history. So the takeaway, the final takeaway is that e-governance is a dual right and responsibility for government and for citizens. And in order to make e-governance work the right way, it's got to be based on trust. And we have to find a way to establish this. Our project is not to say we're going to establish trust, but it's to determine if there is some type of correlation between the effective use of social media and the increase of trust in government. So that's basically our bottom line. So right now we're just open for comments or questions or anything that you see there that you might have a different opinion on. I'd love to hear from you. And Ryan and I will both answer, just direct your question to either one of us. My question has to do with if it's known how many people in a city population or any metropolitan population, how many people actually use social media? You know, is the investment that a government might make in establishing and updating and also, you know, storing that social media records, do they know what part of their population uses it? You know, and that's a very good question and that will make you listen to us track again in the spring. Because the next step of this is to, we have a list of questions that we want answered. We have a form that we're using as a guide. And the information that we can find publicly, we're doing that now so we can give you stats on Facebook and Twitter and all that really. But what does that mean, right? So the next part of it, the questions that are not answered publicly that we can't glean from what we're looking at. We are now contacting representatives from the cities and arranging to interview them to ask them. All right, you have this social media initiative. If you do, you should have a policy. I don't know, but we'll ask them if they do. What are their goals for that? But more importantly, what you bring up, what are the metrics? How do you know that it's really effective? That's the next part of this. So we had, for that part, to be able to ask those questions, we had to put in a request to our institutional review board. And that went in with the interview questions that we'll be asking of the government officials. And then what we hope is that once we identify out of information from the government officials and what we found by doing our own, the two cities in Canada and in the U.S. to do case studies on. And at that point, we will be conducting citizen surveys. And the citizen surveys will be available through the websites of the cities that we select. And they will be asking the citizens their view on the use of social media by the government. And we'll be asking questions, of course. You know, how likely are you to trust that the mayor's office will, whatever it may be that they want them to do, perhaps be financially, I guess, aware of the needs of the city and be able to handle your money well. And so we're going to find that out later. But that's excellent because, no, we can't tell individual participants. You can tell numbers like I could say that was 88,000 people, right? But how do we know how many of them are different? I guess if we go through the Twitter feed, we can. We could go back. We've got all those tweets. So we could go back and try to do that. But we have not done that. What we thought would be more important was to ask the town themselves, those government officials, what they're doing, why they're doing it, how effective it is, and what kind of metrics they're using. So how can they really tell that this is working and it's worth the investment? Because you're right. That's a big problem. It's very costly. Somebody has to do that. So you're using resources, people, their time and the money you're investing in getting this up and running. So excellent question. And I guess I'm saying stay tuned for the answer. We're looking for that. Hello, Pat. And thank you very much for this awesome presentation and you too, Ryan. I just have one follow-up question. I think it's just to congratulate you. And then my first point was that I do agree with you that these Twitter, social media, they're almost diaries. And history books to your point. And I think the whole point of your research project is do we trust them? And I use the word trust in brackets. Because you've given examples of how governors have deleted social media, give given examples of how we can't almost trust the authenticity and reliability of some of the posts that are on social media. So I'm wondering from a very practical perspective as a student, from a records manager and an archivist, if it's our job to catalog these electronic records in the future and somehow preserve this data in the future, just if you don't have to answer this question, but it just might be a thought for the group is do we now have to have additional cataloging rules or additional notes in how we present this data in the future to say, oh, this is authentic. This is not trustworthy. This is not reliable. This was deleted. I'm just thinking in how we present this in the future and how, you know, it's our job to preserve and present and make things authentic and reliable. And people, if we know something is archivist and records manager, that it's not authentic. And it's not our, do we now have to like sort of put that in our cataloging notes. I'm just looking at this, this wonderful work you're doing and how we like, you know, bring it down in terms of in the day to day of the future. What will be our responsibilities? Where we now have to be trustworthy experts in our cataloging and in our preservation? I understand that's a very complex question. I don't think it's that complex because in front, if you turned out your mic, in front of my mind as you were asking that question, I see the picture of Rosemary Woods, President Nixon's secretary leaning over to grab the phone and at the same time pushing her foot down on the panel that then erased the records that were made by him that were recorded. And so there we would say we have a record, but it wasn't complete, right? And how would we know that we'd have to do some investigating. So I think we've always had these kinds of issues now they may seem more complex and more large. But to me, I try to simplify by saying if I were the government of Raleigh, the local government, I am responsible for my tweets, my Facebook pages, my posts. And therefore, I'm not responsible for the whole world. I can take a look at it. And obviously, yes. There may be some posts that are nasty or sarcastic. And that's another thing, sarcasm that we have to look at when we try to determine if posts are positive or negative because they could sound like positive but be sarcastic. But anyway, as that government, I would only be responsible for what I had put out there. Some governments don't even consider comments by others to be part of the record. So what they have to do is have a very clear records policy and understand what they believe would be the record. And then they're responsible for only capturing that and preserving that. And I think if you keep it that way. Now, if you're thinking about that whole Twitterverse, you know, Library of Congress has it and then people can start looking through it and determine for themselves. But as an archivist, if somebody gave me records just like now, I would have to determine authenticity. But I can only do that by whoever happens to be presenting them to me, right? So I would then after that for be responsible for saying they're remaining authentic. They're not going to be altered, whatever. But before that, I have to make a determination as to where I got it from. So you're right, it depends on what we're trying to look at. If somebody is looking globally at the history of the United States at this point in time, I think what they would be doing is saying, this is a picture. This is a snapshot. But unless they really got into who was responsible, who owned whatever social media was being recorded, you couldn't make that determination. Yeah, all you could do is say this is a snapshot of what was going on at this point in time. But I wouldn't worry about that. If I were responsible for records, I'd only worry about our policy, our records and doing that the right way. And I think something else important to consider is the fact that with a lot of these accounts, the citizens will call people out on stuff that they know is wrong. You have so many people who are like doing their research who are always on top of news articles and everything else is coming out. So as soon as they see something wrong, they're going to say something about it. You know, and that is a very good point. That's how a lot of actual stories get broken and that's how some incorrect information that's out there does get corrected because others will respond. And so there's a little bit of it's like Wikipedia, right? Somebody writes something that's not true when somebody else comes in there and corrects it. So there's a little bit of that correction going on. And I think even that is just such an interesting perspective on the way we've decided to communicate at this point in time. Darren, go ahead. Hi, everyone. Thanks for your presentation. So my question is about the part that Ryan presented on about the positive and negative tweets. So I think I'm pretty clear on what a positive tweet would be. Something about services, for example. But I'm not quite clear on what a negative tweet would be. And then the follow-up question is, I think I heard you say that there's some sort of program that's automatically analyzing these tweets and deciding whether they're positive or negative. And I'd just like to hear a little bit more about that. So the first part, I can definitely help you out. Dr. Freight will have to help you with the program that Dr. Chen created. I'm not completely sure on the specifics of that part myself. But for the positive and negatives, like a positive tweet, of course, is something like, thanks for filling the pot hole that was in my road. Awesome. The negative tweet, however, would be like, when people were like, why are you charging us for, why are you charging people to feed the homeless? Like, there were people who were tweeting at Raleigh's government about how horrible this program was. And that would be something that would be considered negative because it's not putting the citizens are in a good mood and it's putting the city in a bad light. Okay. What Ryan said is correct from the sentence point of view. What the researcher is, Dr. Michelle Chen, and she teaches a class in big data analysis, data analysis. She's fantastic. If you have a chance to take an elective from her, you would love it. But basically, what she does is search for particular words in those sentences. So those sentences will come off as being positive or negative as Ryan has explained. But she actually is more granular in saying the word, oh, wonderfully or wondrous is positive. If that's in a sentence likely, it would be a positive sentence. And then you would have to take a look at the context in which it's used. If you had a statement that used the word absurd, for example, or a curse, which is a strange word, or abrupt, those would be negative. They would be considered negative. And what they come from is a lexicon that has been identified and used by other researchers for other projects. So there are just a very large number, a couple, what, 1,500, maybe 2,000 positive words, 2,000 negative words, maybe even three that were used. And what Michelle did, she first thought she could get all of the tweets. We only limited the sentiment analysis is what it is. And we only limited that really to Twitter. We did not do that on the other accounts just because of time. And we did it. She did it for the 20 cities.  They changed that in the spring, right after she did her pilot. And so she then had to find the third party site that had already saved all of the tweets from Twitter and make them available for free. The only problem there is she could only go back maybe a few months or so many tweets. And then she actually wrote her own program that went back again and scraped the tweets and brought them in again. So we actually have all of the statements, just like Ryan was explaining, but they were based on at least one word that appeared to be a word that was negative or positive. Those that were considered neither negative nor positive maybe were retweets. They were something that was done before. They really didn't have much of a message in them at all. So that's kind of how that worked out there. Michelle did a presentation on this for the Siri group. And I thought it would be really interesting if we could get her to do a similar presentation for us in the spring. I think that you'd like to hear that. But basically what she did was look for Twitter data using, you could use Topsy or another kind of application interface. And then she brought it into a data retrieval system, used that in order to get the information and parse it and validate it. So she had a lot of things going on there. And then she had to clean it up, of course. And then she had to look for things like word stemming, you know, if we say something and then we say the same word with an ING or whatever at the end. She had to look for all of that as well. And then eventually she did some charting of trends and plots for us too. So it was quite extensive. But what she used was a Topsy API. And then she created a batch script that was able to retrieve the tweets. And then she used what she called a JSON data file. And it was an XML format. So it was quite a complicated process. It wasn't something you could buy. It was something that she had to go in and actually work on. And I do see her notes here.  And that's what was looked at for scoring. So, yeah, if anybody's interested in the future, we can ask her certainly to do her presentation on her piece of it. It's fascinating to listen to her. Anybody else? Any questions? Okay. Then we're just a couple minutes after. We started a couple minutes after. So I guess we've done our hour. I want to thank you for attending. Thank you very much. And if you have any questions after this, contact Ryan or me and we'd be glad to answer them for you.


I don't know why I was so afraid of it.  They say no. That's it? What? You think God's gonna come down from the clouds? Boom! Hey, everyone! Everyone! Look in that direction!  You know, I think a lot of people that are afraid of rejection aren't looking at the human side of it. Everyone likes somebody. Everyone likes something. You think you're gonna get in trouble? Huh? You're gonna get in trouble? No, it's not abnormal for you to tell someone you think that they're attractive. It's not. But it is abnormal for someone to get upset at you for thinking they're attractive. You think in the opposite way. I used to be afraid of rejection only until a long time ago, you know? It was at this one cafe, me and my friend usually go to, right? And there was this one girl. Beautiful girl. I'm talking about Cinderella-tier woman. And the funny thing is I'm not really even into white women like that.  Okay, time out, time out. Post-edit kneecaps here. I feel like this could be taken poorly. It's not that the nigga kneecaps doesn't find white women attractive.  And I've grown out of it, you know? Nowadays, I don't really have like a racial preference. I guess you'd call it. So it's not like I'm saying white woman bad. It's just that I'm not running towards them like that bird nigga from off the Looney Tunes, right? I presume. I didn't even feel the urge to kiss them or anything, right? I legit thought I was gay for a little bit. Not gonna lie. And also, ever since my two favorite albums hit me with the de-cunification, right? The white girl fetish I had just got thrown even further down the toilet bowl. But back to the girl, right? It wasn't just that her face was beautiful. She also had these real thick, aggressive eyebrows.   I think maybe it might be because all the strong woman in my life, like my mom, my sister, they also have like these real wide, angry-looking eyebrows. And maybe I subconsciously equate strong eyebrows with strong maternity. So what happened is that, and I'm sure a lot of other people can relate to this, but I don't know if she was just being nice to me, but she complimented my necklace. She's like, I like your necklace. It's dope, right? That's the way she says it, right? And as you ladies know, us guys, that's pretty much all the skills you need to make us fall in love with you, right? Give us compliments and make us feel loved. That's it, right? So I'm thinking, huh, maybe she likes me. I have no idea. I'm not super experienced in relationships and dating people, but my friend, he's like, hey, bro, I think you should ask that girl out. And I'm like, huh? Her? Heck no, nigga. She is way too pretty. You see, this was before a nigga hit that late puberty, early 20s glow-up. Follow me on Instagram. And I was an emotionally sensitive nigga. Ain't no way I'm gonna be able to recover from getting rejected from a woman of that caliber. Okay? Day ends, right? Some days go by, me and my nigga, right? We head back to the cafe spot. The girl's there again and we order and as we're ordering, she's like your phone case looks really cool. And on the outside, I'm like, oh, thanks.  I wish I had better social skills to engage in a proper conversation with this woman. But we go and we sit down on the couches in the cafe and my friend's like, bro, I think you should ask her out. You should ask her out. But I'm not having it, right? I had so much self-hatred for myself back then.  So I leave the cafe defeated, defeated. And we head to the mall the same day. My boy, right? Star sign Leo. So you know this nigga's on the prowl. He finds this one pretty girl at this, you know, this one shop that sells animation, right? A woman behind a counter. She kind of tall.  And he's like, hey, bro, I'm about to go ask her out. And I'm like, I don't know about that, bro. I think I know that girl. I think I've seen her with a boyfriend once or something like that, right? But I don't know for sure, right? I don't know for sure. But even then, the chances of homeboy getting rejected have only increased. They've only increased, but he still, he still doesn't seem swayed in the slightest, right? He's like, nah, bro, I'm about to go ask her out, right? And I ask him, did you want me to leave or something?  Do you want me to leave?  It's just that I'm a very emotionally sensitive person. And seeing my friends in a bad mood also makes me feel really bad, right? But he's like, no, you don't have to leave. And I'm like, oh, okay. And I'm glad, you know, I'm glad I didn't leave or else I wouldn't have grown from this experience. But what happened is that he tells the girl, hey, I think you're really attractive. Do you have an Instagram or something I can get, right? And the girl's like, I have an Instagram, but I do have a boyfriend. And I'm like, damn, that's gotta hurt. But I look at my nigga's face, right? And he doesn't seem phased in the slightest. He actually looks a bit entertained.  Well, thank you. And, you know, we start strolling through the mall, like nothing ever happened. And I'm like, that's it? Really? That didn't seem so bad. You know, the girl was real nice about it. My friend was real nice about it. If anything, I think the rejection only made the day better. Because think about it, right? It's already a no if you don't ask and you're going to go home with that uncertainty in your spirit. All right? All right? Maybe that girl also thought I was attractive, but now I'll never know. But after getting rejected, it's like, I know for certain that girl wasn't interested. And there's nothing wrong with that. Don't take it as a personal attack, you know? Even the prettiest of niggas get rejected. But continuing the story, I see my boy get rejected. And I'm like, yeah, that doesn't seem so bad. And it inspires me, right? It inspires me. He's always inspired me as a person with the amount of confidence he's had. Dude always seems so fearless.    I want to try again.  So we drive back to the cafe and the girl's still there at the counter.  So I'm sitting there on the cafe couch shaking in anxiousness because my body's telling me, stop, go, stop. Go, stop, stop. Stop, go. So I'm just petrified, not really knowing what to do. And then there's this one woman that comes in. She's taking pictures and stuff like that, right? I thought the woman behind the counter was beautiful and she still was, right? But this woman had everything.  Wasn't even just her face, her body, the aura she had around her. And she also had this like real pretty natural red hair. And you know, I'm not usually the type of guy to try to degrade women based on their sexual features, but dog. This woman's cake was astounding, astounding my nigga.  Ain't no way, bro. She had to have like some sort of Hispanic or Egyptian bloodline mixed in with her. Maybe her great, great grandmother was African or something because my God, what a beautiful body she had. And I'm over here marveling. Just marveling.  He on the prowl. He tells me I'm about to ask that girl out and I look at him and bewilderment. Are you sure? Are you sure? The amount of grief. The amount of grief I'd be and if I got a note from that woman would be catastrophic. But again, this nigga's confidence. He just don't care. And I'm thinking, wait a minute. This nigga just got rejected not even an hour ago and he's already back on his feet. That's how you're supposed to do it. Take an L and just bounce back like that. Where's the seething at? Where's the internalized self-hatred at? This nigga just didn't care. He just doesn't care. But I'm sitting on the couch while he's talking to this redheaded goddess, right? This goddess, right? Let's get that straight.  Let me go play some flappy bird on my phone. Some unofficial flappy bird rom. I had to download off the internet, right?  He ain't even saying nothing. And I'm like, no way. He's like, yeah, yeah, yes. I plucked it. Bro, the size of that W, the size of that W was so large. I don't even understand how we had the strength to walk back to the place we were sitting. The amount of back pain I'd be in from hauling that W around with me would have been excruciating. And I see this. I see this friend of mine that's always been there for me, always inspiring me. I see him do what I've never had the strength to do and it lights this fire in me.  This is also for my boy, you know what I'm saying, right? And I'm walking towards the counter and behind two women and as one woman goes away, I can feel the heat, the heat and pressure increase inside me. And now there's only one other woman in front of me. My heart's racing. I feel like I'm breathing through like a tiny-ass coffee straw or like tea straw, whatever the hell it is, right? Bam, another woman goes away. Now it's just me looking at the girl and she's like, what would you like?   I don't really remember the exact quote, but she's like, what would you like? And I tell her, oh, I'm not getting any coffee. I need him over here. I'm talking about this one guy, tall-ass white dude that always says, what's up to me anytime I come into the cafe. And not in like a four-sway or nothing like that. You can just tell that he's like a, he's like a real social genuine dude, right? So she switches stations with him and he's like, what can I help you with, man? And I'm like, I'm sorry, bro. I also need her.  And he's like, oh, okay. With a smile, you know, and I think he already knew what I was trying to do, right? So he calls her over here, right? And she's like, yeah.  The most beautiful moment of my life.   And she smiles real nicely. And she's like, thanks. But I hear something in that. Thanks, right? It sounds a lot more friendly than it does provocative. And I noticed this and I say, but I'm guessing you already have a boyfriend. And she's like, yeah, I'm actually married.  I see. Well, thank you. Thank you, miss. And I meant it. I truly meant it. You know, I always thought rejection was so bad. I always thought there'd be like some really bad reaction afterwards. But no, all I felt was peace, true peace. And as I walked back from the counter towards my friend, there wasn't anyone clapping for me or anything like that. But I could feel inside me, my soul dancing, applauding itself, feeling itself being freed. And as I headed back to where my friend was sitting, right? I see him and he has like, I'm guessing he already has like an idea of what happened.  Not to mock me or anything, but an extremely proud smile on his face. Humboy didn't even have to open his mouth to say it. But I knew exactly the words he was thinking on his mind.   How am I looking today, boys? Huh? How am I looking today? You ain't even got to tell me. How do you know I'm looking snazzy? I'm looking real snazzy.


From Hollywood. It's the Dennis Day show Yes, it's the Dennis Day show produced and transcribed in Hollywood with George Wile in the orchestra and Dennis special guests Vera Allen and Johnny Mercer and now here he is the star of our show Dennis Day Ladies and gentlemen music and song player pretty important part on this show And if it weren't for the songwriters my program might sound something like this and here he is the start of our show Thank you folks and good night So that's why I thought it might be interesting for you to meet one of the men who makes any musical show possible One of America's top songwriters that pixie from Dixie. Mr. Johnny Mercer Thank You Dennis. I'm very grateful for that introduction Well, you deserve a Johnny after all you've been pounding the piano and the typewriter for over 20 years Banging out music and lyrics that have become hit after hit say Johnny Would you mind letting me have a look at those talent loaded fingers of yours? Not at all here Well, what do you know? Dr. Scholl's footpegs on your fingertips Well, without them my songs would have been awful corny Are you sure your writers made you turn over a new leaf. I know what you mean Well, John you've written such great songs as black magic dream Blues in the night and people all over the world have hummed and whistled your tunes But you know many of them don't know much about you personally So tonight we will present a capsule and also a tablet version of your life Johnny Mercer entitled Is your past you all You were born Johnny Mercer in Savannah, Georgia on your father's tobacco plantation The first time your father saw you in your crib. He looked down and exclaimed Which means I've been looking at babies for now in a 40 year and I've never seen one so round so firm so fully packed As a very young man your genius for rhyme and rhythm soon became apparent on your first day at school You looked at the blonde blue-eyed and beautiful school teacher and you said Teach your teacher. You are zoot and I dig you cuz you're cute Man, it really would be cool if you kept me after school After being expelled from school You went to work on your grandfather's farm Let's go back to those days and show how working on the farm Inspired one of your early song hits I gotta go out milk to go. Oh Do you like goat's milk?  Nobody in the family likes goat's milk Well, then Johnny boy. Why do you milk the goat? The goat don't like milk either And Johnny Mercer's dislike for milking goats caused him to write one of the biggest hits of his career I'm an old cow hand and so it was quite a pull Johnny Mercer before you went to New York to try your luck The first person you go to see is the famous song publisher Saul Hartburn Mr. Hartburn, I have a little song which I think has a chance of becoming a hit. Well in that case you come to the right place We publish all the hit songs of all the great composers this year we publish togikar Michaels matzadas Jimmy McHugh's I can't give you anything but latkes, baby And oiling boil ends. I'm dreaming of a white white fish All right, mr. Mosher. Let me hear your song there, Dawton. Okay. Here it is Pardon my southern accent Pardon my southern draw It may sound funny. Oh, but honey. I love you all Hey, what an accent he's got Just a minute look it's a good song, but the voice mr. Mosher When you write a song you should use as few words as possible. I'll show you what I mean sing it again, please Pardon my southern accent. Look look. We all know you got a southern accent. So take that out Pardon my southern draw If you got a southern accent, you got a southern draw too. So take that out also It may sound funny if a man from Savannah, Georgia talks to a man from the Lensis Street It's gotta sound funny So take it out. Oh About honey in this office. No, honey. Borscht. Yes Like some bagels. Yes, man. A chevrolet's gefilter fish. Yes, but honey I love you all wait a minute when a man really loves he loves one not all Now mr. Mosher sing me the song the way that I fixed it up Jeepers creepers. That's it. And jeepers creepers magic and those peepers I told you mr. Mosher. I'd help you get a hit song You're on the way Johnny Mercer and hit follows hit songs like lazy bones Here comes the British weekend of a private secretary and the angels sing come rain or come shine black magic and many many others They're proud of you back there in Savannah, Georgia Yes, Johnny Mercer in that peaceful southern city your name is being drawled on everyone's lips But success hasn't changed you you're still the same sweet unspoiled Johnny Mercer you always were Then Hollywood beckons Hollywood the land of glamour the land of romance The land of such motion pictures as Betty Gravel in three for the show and Richard Barthamus and Tollable David Hollywood now what do you think happens next Johnny Mercer? I don't know. I haven't had a line for so long I sort of lost interest You're on your way to Hollywood on the super chief and on the train comes the inspiration for still another great Mercer composition. That's right I was riding in the club car when suddenly I heard clickety-clack clickety-clack clickety-clack You mean the rhythm of the wheels on the track.  I reckoned it was engine number 49. Yes It's the only one that sounds that way on the Atchison to be here and the sound of pay Well, no this time the train happened to be the Baltimore in Ohio Beano. Oh, what great piece of music did you write about the bee and oh listen?  Oh just fine Johnny boy for the last 30 years I've been thinking about you back home while I've been sitting in my old rock and chair Just a sitting in a rock and but grandpappy. You don't have a whole rock and chair.  Heartburn Jeepers Creepers. How are you, John? Hello, how are you grandpappy sniffers a Billy goat Johnny boy? And to bring Johnny Mercer's great story up to date here He is singing his latest composition written for MGM seven brides for seven brothers lonesome pole cat Ladies and gentlemen, we have a special treat for you now the beautiful and talented Metrogolomere dancing star miss Vera Ellen. Thank you, Dennis. Well Vera. I mean Ellen. I mean Say I'm a little confused. You have two first names. Oh, no Dennis. My name is Vera dash Ellen I don't blame anyone for making a dash after Vera Listen Dennis before we go any further. I think I should tell you something of vital importance. What is it Vera Ellen? What is it? Vera Ellen appears by arrangement with metro dash Golden dash mayor whose newest production in cinemascope color is Jupiter's darling starring Esther Williams Howard Keele and Marge and Gower champion. We're a little late folks. Good night Say isn't that the movie that has all those colored elephants in it? Yes There's a yellow elephant. Mm-hmm pink elephant a blue one a green one and a red one You know, I remember one scene where the elephants were all herded together How is it that the color of one elephant didn't rub off on the other? Oh, I thought you knew Dennis They were hazel Bishop non-smear elephants Oh Enough about Sabu's Nash Rambler. Let's talk about your dancing talents. How did you get started as a dancer? Like every other dancer, I guess I took lessons. I'll bet you had a very fine teacher Well, not at first. Let me tell you about my experience with my very first dancing teacher. Okay Miss Vera Ellen, you are in the presence of the former dancing master Yeah, but a dirt under a shower to jet a Dennis day Now what can I do for you? Well, I've come here to learn dancing Certainly put your arms around me and pay strict attention because from this I make my living All right, maestro. Hold me tighter. Oh Tighter Tighter than that even Do you call this dancing? No, but that sure is living Well, uh, maestro, let's get started with a lesson Do we wait now the old dancing master will show you a very basic and simple step Watch me closely first. I extend the right arm next. I extend the left arm Then I lift up my right leg Now I lift up my left The old dancing master hasn't been able to master that one yet But ma'am cell I'll call you as soon as I do or what? Well, you see Dennis my first experience with dancing was quite unusual Oh to say the least but you know, you've come a long way since then tell me. What are your future picture plans? Well MGM is scheduled another musical for me, of course. Oh sure There'll be plenty of dancing in it and lots of songs. Did somebody say songs? Why Johnny Mercer? What are you doing here? As long as you need some songs for your next picture Vera I thought maybe I could make a bid for the assignment. Yeah, you know Johnny and I are working together now And we're on a very unusual assignment right at this moment. Oh really? That's right Dennis and I are engaged in a musical project that will make the teenagers appreciate literature more. Oh That sounds fascinating. Well, come on. Tell me more. Well, here's the idea We think that the high school kids might get more interested in the great works of literature if somebody wrote some songs about them Sure, if pictures and plays have theme songs, why can't books Johnny sing that first one? We wrote you know the one based on that bestseller the power of positive thinking, okay? the power of positive thinking There's power and positive thought if your wife wants to make you can tell her to think and you'll think her in the thinking it was bought Say that makes a lot of sense. I think Well, do you have any others? We certainly do Dennis sing of the one about the tale of two cities, okay? A tale of two cities Their woes and their pitties is a tale that brings tears to your eyes Every time to cities of weepers with sad red rim peepers When they smudge in Azusa, they're smogging anaheim Well, you're certainly giving Charles the dickens well What other bookworm bop have you cooked up? Well, we've got a little mumbo based on the book called flying saucers here it goes Flying saucers come from Jupiter. That's the story scientists prefer but there's flying saucers every night when the couple next door start to fight Well that one ought to make everybody up on Mars go to Well, that's a very admirable project fellas But when I think of Johnny Mercer, I think of such songs as Accentuate the positive or is Oscar-winning song in the cool cool cool of the evening and the haunting one Laura And when I think of Dennis Day, I think of beautifully sung ballads Oh Mercer well, I guess that's it for tonight Don't forget to tune in next week when our guests will be mr. Jose Ferrer and mrs. Jose Ferrer Rosemary Clooney join us then, won't you this is Vera MGM for Metro Golden mayor Ellen and Johnny AT&S F Atchison Topeka and Santa Fe Mercer And Dennis Day saying We saw one and God bless you stay show is written by Irving Taylor and Alan Wood produced and directed by Fred Levin This is Jimmy Wallington speaking inviting you to join us next week for the Dennis Day show Good night. This is the United States Armed Forces radio and television service


So for the last 40 years, our community had developed hundreds of block ciphers, but if we look at all those designs, 99% of them follow a very simple design idea, namely take a relatively simple round function and iterate it over and over again with some key schedule. And we have two basic ways how to choose the round function. We can either use regular networks or SP networks, even though I'll not use the fact that there are S-boxes and linear mappings, so you use an invertible operation in each round, or you are using a five-stell structure in which you divide the input into two parts, not necessarily equal, and you apply a not necessarily invertible function to one and then xori to the other side. This is basically what we have been doing for the last 40 years, and the fundamental question in my opinion is to try to really understand how much security do we gain by iterating a good round function over and over again. So I think that after 40 years of analysis, we should have reached some conclusions about how security accumulates as you increase the number of rounds. In the case of indistinguishability, information theoretic analysis, Jacques Pateron had done a great job in trying to understand, as you increase the number of five-stell rounds, how close it gets into a poly-rendum function. But if I have to summarize the situation, you know that Gauss in his famous book wrote that prime numbers are such fundamental items that the dignity of mathematics requires that we understand them, understand the distribution, understand how to distinguish primes from non-primes, etc. So paraphrasing Gauss, I would say that the dignity of cryptography demands that we understand what happens when we concatenate several rounds on top of each other, assuming that each round by itself has no weaknesses. Now, there were some recent surprises in developing generic attacks on such generic structures, those which do not look at all into the internal properties of the round function. So at Crypto 2012, the same gang of researchers presented improved generic attacks on all regular networks, those which are not five-stell, with at least four rounds. So any four and higher number of rounds suddenly had better attacks than previously known. And what I'm going to present today is a similar kind of improvement, where we use new techniques to develop improved generic attacks on all five-stell networks with at least five rounds. So altogether, since most of our designs have more than four or five rounds, we are getting new improved attacks on the majority of structures when we ignore internal properties. So the new generic attacks are actually so efficient that they even improve the best-known concrete attacks on a variety of cryptosystems. So here are some examples. DEAL 256 is a design with eight rounds in which each round function is extremely strong. It's a full DES. This was one of the proposals submitted to the AES competition. So because the round function is full AES, we can think about it as a kind of random function. And by using our new techniques, which work generically, we can improve the memory complexity of the best-known attack on DEAL 256 by a large factor of 2 to the power of 56. Another example, in the case of CAST 128, we can reduce the memory complexity again by a large factor of 2 to the 47 and no better attack is currently known. So the basic cryptanalytic problem is the following.  All the attacks I'm going to describe are not in the chosen, but in the known plaintext model. And typically, we are going to talk about a small number of plaintext-cypher-text pairs. And the goal is to find a key that maps all the plaintext into cypher-text. And we can assume that the plaintext and cypher-text are n bits long, and there are r rounds, and that each round gets an independent n-bit round key. And therefore, the total number of keys, or key bits, is r times n. And information theoretically, if everything is random, you expect that after seeing r input-output pairs corresponding plaintext-cypher-text pairs, then the rn bits of the key are likely to be uniquely defined. And most of the attacks I'm going to look at will deal with this minimal number of rounds, minimal number of data, minimal amount of data. And later on, I'll mention what happens when you are given more data. Okay.  XOR a key and apply-round function. I'm talking about the most general case in which, in each round, you are mixing together in a random way the n-bit key with the n-bit input. So we can think about the problem as an execution matrix where vertically I think about applying the r-rounds. So here is the plaintext, first plaintext. I'm applying the first round, and then I'm applying to the result, the second round and so on, until I get the first cypher-text. And here is the second given plaintext. And all the columns are independent of each other because I'm starting from arbitrary known plaintext, no relationship between them. And also, all the rows are independent because the first key and the second key and the third key are all assumed to be unrelated n-bit round keys. No key schedule here. Now, if you are talking about a single round, there's nothing better you can do than exhaustive search. It's easy to show that this is optimal. So basically, the time is 2 to the n. You have to go over all possible keys for a single round, and the memory is constant. Once we go to two rounds, already something better can be achieved, better than exhaustive search. And this was a very nice idea that Diffie and Hellman published in the late 70s, invented in the late 70s, published in 81, which is the Meet in the Middle Attack on Double Encryption. And the result is that double encryption with two independent n-bit keys can be broken with the same time as a single encryption, but at the cost of enlarging the memory also to the n. And I'll very quickly just show you the basic idea of Meet in the Middle. So for each n-bit value of k1, you partially encrypt the first plaintext. You can do plaintext because there are two keys. So you are given p1, p2, but let's ignore p2 for the time being. I take p1, encrypt it under all possible keys k1, and I'm getting 2 to the n possible suggestions for the value in the middle x. Then I'm keeping this table, but sorting it, not according to the order in which I generated it, which is going over all the k's, but in the order of this intermediate value x. So I can quickly search for any desired value of x in this table. Table of size 2 to the n. Now I take the first ciphertext, decrypt it under all the possible k2s. For each one, I'm getting a suggestion for x, which I search in the table, and therefore I get a suggestion for a corresponding k1. Usually unique, sometimes there are a few. And therefore you are now going to get each k2, one, or maybe a small number, of corresponding k1s. You take the pairs of k1, k2, which are suggested, and check their validity based on your second plaintext ciphertext pair, and only one of the 2 to the n suggested combinations is likely to survive this second test with the second pair. So this is a well-known technique, nothing new here, time, as I said before, is 2 to the n, because you're separately encrypted here under all the possibilities and separately here, and the memory is the size of the table 2 to the n.  Motivated by three key triple days, people had looked very, very extensively at the security of triple encryption with independent keys, unfortunately the only idea that people came up with is guess the first key, then you reduce the three encryption into two encryption, and then do meet in the middle. So basically you increase the time from 2 to the n to 2 to the 2n, keep the memory the same, because for each guess you can reuse the memory, and the product of this time for each memory is still the same as the number of possible keys. Okay, so it looks as if we fully understand one, two, three rounds, and then surprise in 2012 was that as soon as we get to four rounds, suddenly there are more efficient algorithms that you can apply. So we shouldn't have stopped at three. So in meeting the middle attacks, time times memory is equal to the number of keys. So this can be viewed simply as a trade-off. If you want to decrease the amount of time by certain multiplicative factor, you have to increase the memory complexity by the same factor. You just shift from time to memory. And until recently most people believe that you can divide not in the middle, do all kinds of things, but basically time times memory should be equal to the number of keys in generic. But in 2012 we showed that there's a much richer theory behind it, and in fact I'm going now to start by recalling the simple proof that four-round encryption can be broken with the same time and memory complexities as breaking three-round encryption by using something which we called a dissection technique. So what's the difference between meeting the middle and dissection techniques? In meeting the middle, I'm guessing keys at the top, I'm guessing keys at the bottom, I'm encrypting from the top towards the middle and decrypting from the bottom towards the middle, and I never know what is the value in the middle. I'm using it only as a filtering condition because it should be the same, whatever it is, it should be the same as you come from top and bottom. In dissection attacks you use a different idea. You guess what is the value in the middle. Not all the way through, but some of the values in the execution matrix. What does it enable you to do? It enables you to partition the problem into a problem with known plain text ciphertext with a reduced number of rounds at the top and also a partial problem of known plain text ciphertext pairs at the bottom. So now it's a completely different kind of recursion. If I have to think about what is the effect of guessing a key versus guessing a value, if I guess, for example, the first key, I reduce it, the problem for r rounds to r-1 rounds, but now I know all the plain text and all the ciphertexts of an r-1 cryptosystem. If I guess a value somewhere in the execution matrix, then I get a partial, a partition into two partial problems with a top part, so you have k, let's say, t rounds here and r-t rounds there, and each one, you know, some of the plain text and some of the ciphertext. So it's a different idea, and very quickly in dissection of the text, for four rounds you guess the middle value in the first plain text to ciphertext execution. This enables you now to solve this through meeting the middle, you get some suggestions, and now you go and verify them by looking at the second plain text ciphertext. You'll see more examples once I get into the new text. So I'll skip the details, you can see it in the paper. So the total time is 2 to the 2n, and the total memory is 2 to the n, which is the same as in triple encryption. So I went from three encryption to four encryption, but didn't increase the complexity of either time or memory. So dealing with a larger number of encryptions, if I go to five rounds, the best thing we know how to do is to guess the fifth key, fifth round key, and solve with dissection the four round. Six rounds, the best thing we know how to do is guess two keys, and then solve again by dissection the four remaining rounds. So it looks as if it was a one-time lucky event that going from three to four we didn't increase the complexity, but in fact, attacking seven rounds turns out to have the same time and memory complexity as six rounds. So again, I'm saving, and the savings start to accumulate, because once I'm taking seven, I had the saving when you went from seven to six, and also the saving when going from four to three. So things get better and better, and the attack on seven rounds is based on dividing it into unequal parts, three at the top, four at the bottom, guessing two values in the execution matrix. This makes sure that the number of possible triplets of keys where two of the intermediate values are known. There were two to the three N possible keys, but I'm imposing two to the two N conditions, so there are only two to the N possible triplets of keys, small enough so that I can store it in two to the N table, and then at the bottom, I'm making recursive use of the four-round dissection technique. So this will require guessing another value in the middle. So what you are going to get is the following, skipping the analysis. For seven rounds, you get time, which is two to the four N, memory, which is two to the two N, so the product is two to the five N instead of the number of keys, which is two to the seven N because I saved twice in terms of going from three to four and going from six to seven. So there is a whole magic sequence of ours for which such a saving happens. When you go to three to four, when you go from six to seven, when you go to ten to eleven, then sixteen, twenty to twenty nine, these are the places where our recursion saves and you accumulate the savings. So this was very strange property, but now let's switch to the Feistel structures. So in order to compare the meet in the middle and dissection approaches on Feistel structures, we have to understand why meet in the middle is more effective on Feistel than on regular networks. And for the sake of convenience, we assume that the round function has only half the size input, so N over 2-bit inputs, N over 2-bit outputs and also N over 2-bit round keys so that guessing a key and guessing a value will cost me the same, otherwise it's harder to compare. So I can always consider a pair of Feistel rounds each with N over 2-bit round key as having one regular round with a full N-bit key. Now let's look at how you attack meet in the middle with an odd number of rounds more efficiently because you can totally ignore the middle round. Why? You guess the first three keys so I can encrypt from the top and get the value here, both this value and that value. I can guess three round keys from the bottom and again calculate those values, but due to the Feistel structure I can equate on half the state and therefore I don't have to guess anything or to do anything about this key of the middle round. So I get a middle round for free. That's why meeting the middle is better for an odd number of rounds than normally. And this is where we were stuck for three years between 2012 and 2015 because our dissection didn't have the same kind of improvement where you could skip the middle round. So let me summarize what are the two complexities. Meeting the middle attacks for seven rounds require 2 to the 1.5n that's how much time you need to guess three half n-bit keys. So the time-times memory of meeting the middle on seven rounds is 2 to the 3n and dissection I can think about it as four regular rounds each one being two Feistel rounds so the time for a four round attack is 2 to the 2n memory is 2 to the n so again time-times memory is 2 to the 3n no improvement of dissection over meeting the middle for an odd number of rounds. However, here are the results of our improved attack so I'm quoting the previous ones so meeting the middle had 1.5 1.5 dissection had 2 and 1 the product was 2 to the 3n and our new attack gets the best of both worlds 2 to the 1.5n which is the minimum of the two and the memory is 2 to the n which is the minimum of the two. Okay, I think that I'm going to skip quite a large number of slides now I'll just give you highlights of the basic idea so we are looping over each possible n over 2-bit value of this value R3 which is about halfway through the 7-round encryption for each one of them we prepare a table which consists of 3 plates L2 and R2 and K3 which had been pre-prepared in a way that I don't have time to explain and the size of the table is 2 to the n and I'm going to do a more sophisticated meeting the middle with dissection and I'm going to get the improved result that I mentioned before Okay, here is the magic sequence that we now get for Feistel structures as I increase the number of rounds again and again I'm going to get points at which I'm suddenly not paying any complexity any added complexity for the added Feistel round so the original magic sequence for regular SP networks and for Feistel network our new techniques are giving us improvements at 5 that's why I'm starting to get improvements only from 5 and then 10, 15, 22, 29 a different sequence now let's keep the multi-collisions let me show you a table which summarizes our improvements so for 5 rounds the minimum for which we get an improvement could give you 2 to the n and 2 to the n because you are guessing 2 half n round keys from the top and 2 from the bottom separately if you are using slightly different partitioning you get 2 to the 1.5 n and 2 to the 0.5 n in both cases the product is 2 to the 2 n our new attack is 2 to the n and 2 to the half n the product is 2 to the 1.5 n for 7 I already showed you how we get a product which is 2 to the 2.5 n whereas all the previous attacks were 3 n for 8 the product here is 3.5 with this section I could get 3 and with a new technique I can get ok this is also 3 so compared to 2 to the 2 n if you don't want to use the smallest possible amount of memory you are willing to have more time then you can reduce it from 2 to the 2 n to 2 to the 1.7 n 7.5 n and get something which is better than 2 to the 2 n here for 15 just quickly here it's a product 2 to the 7 n 2 to the 6 n for the section 2 to the 5.5 this is a new and if you are willing to have a little bit more memory then you are going to get 5.5 here ok conclusions and open problems so we presented several new generic cryptanalytic algorithms which generalize dissection attacks from 2012 we had to change when we moved from regular networks to freestyle networks because we had to fight the fact that meeting the middle is slightly more efficient for freestyle and this allowed us to improve actually the best known concrete not the generic attacks on several block ciphers like deal and cast especially those who had relatively few rounds of relatively strong ground functions the main open problem while we keep improving and finding new attacks it is we have no idea how to prove the optimality for our attacks so it would be extremely interesting to look not at the information theoretic question of distinguishability from random oracle but the cryptanalytic problem of finding the keys key recovery attacks can you show that generic key recovery attacks on a certain number of rounds can never be better than anything thank you very much


This morning at the church is really my theme song and I would love to give y'all some of it it says I've been healed by the Savior And I've felt fire from above And I've been down to that river And I ain't the same. I'm a prodigal's return And all of my hope is in Jesus And thank God my yesterday's gone And all of my sins are forgiven Yes they are. And I've been washed by the blood I'm no stranger to the prisons I've worn shackles and chains But I've been freed and forgiven Yes I have. And I'm not going back I'll never be the same That's why I sing all of my hope is in Jesus Thank God my yesterday's gone And all of my sins are forgiven And I've been washed by the blood Thank you so much man. All right now. All right now. Save man. That's what it's all about man.  That's what he done. He snatched you from a place where you could have died in your sins Yes, sir. But you was delivered. And now God has used you and others are being delivered. Yes And you just don't know what God is going to do. See your testimony was just a test and you went through all of that stuff and you still hear a lot of your friends didn't make it Yes. And you hear. And so with that being said there's a reason why...


Hey Golden Bears, I'm Julie McEwen and I'm Devin Founsley and today we are at the Clarkhurst Sand volleyball course. Today we're going to get an inside look with freshman sand volleyball players, Sammy Furley. Let's check it out. So, Sammy, last semester you played indoor volleyball for the Bears. What has the transition been like from indoor to sand? Well, it's been super fun. I've always loved playing on the sand. I grew up doing it. It's really nice being outside and, you know, getting the fresh air and sunlight every day. But it is tough.  Not only are you in the sand, but it's also only two people. But the work put in is very much worth it. And it was also recently announced that the sand volleyball team at Cal had the highest team GPA on campus. What do you guys do to maintain such high GPA? No skipping class. Everyone's just super great about staying on top of their work.  That's what we are. We're here to work and on and off the court. It's a really good goal for us to have to, you know, be the top and be the top in everything we do. All right, Sammy. So we know that athletes travel a lot. So we were wondering what's your favorite part about road trips? Oh, man, it's hard to say. I love traveling with the girls and, you know, hanging out with them and stuff. Being away from school, too, is really different. You don't normally get that with this many friends and this many people. It's really fun to get to know the other girls and have fun. Tell silly jokes and all that.  We had a great conversation with our coach, Nicole, and, you know, it's good bonding experience and all that. So is there a specific road trip you're looking forward to this year? Yeah, I'm really looking forward to Hawaii. We leave on Wednesday and it's going to be super fun, super hot. But, you know, I've played in Hawaii for high school tournaments and it's always a good time. We have some girls that live there, so we're going to do all the local stuff. And I just can't wait to be there with everyone hanging out. And also, if we make it to Bama, Gulf Shores is the end of the year tournament. So I'm really excited for that as well. That sounds like a great time. All right, Sammy, so what's your favorite part about being a student athlete here at Cal? I think it has to be with a prestige that comes with it and maintaining it. You know, it's hard to say that we are here as students and athletes. You know, it's really a tough job that we have, but being here supporting our team and, you know, just supporting Cal as a whole is so, so fun and so nice to have on our shoulders. Like, we're here in the class and on the court always working hard and just proud to be a part of it. Well, thank you so much, Sammy, and have a great rest of the year. Thank you. That's all we have for this week's episode of Cal State Sports. Make sure to come check out Sam Volleyball, Clark Crane. Go Bears!


Good morning. Yesterday, the Defence Minister made a statement in both houses about the situation on the border in Ladakh, which I know. There are a couple of things that need to be made absolutely crystal clear. The first thing is that the Indian government's position at the beginning of this was status quo ante on April 2020. That is what the government was negotiating for. Now, sheepishly, the Defence Minister comes and makes a statement. And we find that Indian troops are now going to be stationed at finger 3. Finger 4 is our territory. That is where our post used to be. So now we have moved from finger 4 to finger 3. Why has Prime Minister Modi given up Indian territory to the Chinese? This is the question that needs to be answered by him and by the Defence Minister. First, second, why have Indian troops, after the hard work that they did capturing Kailash Plains, ranges, why have they been asked to move back? What has India gotten in return for this? And most importantly, the more important strategic area, Debsan Plains, why have the Chinese not moved back? These are the real questions. Why have they not withdrawn from Goghra and Hot Springs? It's a very clear thing that has happened. The Prime Minister of India has given Indian territory to China. India's land, the sacred land, Narendra Modi has captured China. This is the truth. The negotiating position of the Indian government with China, the status quo, in 2020, April 2020, he forgot the government, left it and threw it away.  He has bowed her head. Our land is till finger four. Narendra Modi has captured India's sacred land from finger three to finger four. This is the first thing. Second, the strategic area of Debsan Plains, where China has come in, First of all, there was no strategic advantage. The Chinese were in our land. The Chinese were in Debsan. They were in Pangong. Our soldiers risked everything they had to go to Kailash ranges. That's where the strategic advantage is, any rose. Now the Prime Minister is given back the land. Status quo and tea is irrelevant. Kailash has been given back and nothing has happened on the key area which China wants, Debsan Plains. This is absolute 100 percent cowardice. There's nothing, there's nothing else. The Prime Minister is a coward who cannot stand up to the Chinese. That's the fact. And he is spitting on the sacrifice of our army. That's what he's doing. He's betraying the sacrifice of our army. And nobody in India should be allowed to do it. Nobody in the rest of the world should be allowed to do it. That is the fact. And yesterday the Defense Minister is giving a little statement silently, sheepishly. Why didn't the Prime Minister come and say this? Why is he, why is he making the Defense Minister make this statement? The Prime Minister should say, I have given Indian land to China. This is the truth. Thank you, sir. Siddharth from A&I. Sorry, what are you asking? I just said, you think I got the question. Look, the question is, this is the land of India. Narendra Modi has given the land of India to China. This is the question. The reason is that Narendra Modi couldn't stand in front of China. Thank you, sir. Uma from NDTV. We were not allowed to raise it. And I'm sure we will not be allowed to have a debate on it. 100%. Arun from TV 18. No, not India. But they have come into our house. The whole world is saying that China has come into our house. And we have given them our house. The main thing is that our Indian mother was up to finger four.  And Narendra Modi has captured China. This is the reality. Ashish. Okay, tell me. The gift is clear. The gift is clear. Fingers three and finger four are given. The gift is clear that they are sitting in the dip-sang. The gift is clear that they are in Gogara and the hot spring. Tell me the take.  No, tell me the take. You talked about the give take. I said the give. You tell me the take.  Because the take is not clear. The give is clear. The Prime Minister couldn't stand in front of China. I think people should be enraged about this. I'm surprised that the press is behaving in the way it is. This is absolutely absurd. You have a responsibility to raise these things. I have to go now to Rajasthan. I am saying that it is the responsibility of the Prime Minister to protect the territory of this country. The Prime Minister has ceded Indian territory to the Chinese. It is his responsibility to solve that problem. How he does it is his problem, not mine. Thank you.