Reflection 11/7

Summary 

This article discusses how email archives can be visualized to show individual relationships over a span of time based the frequency of and distinction of the words used in the interactions called Themail. They discuss other similar programs created to analyze email archives, but this is the only program that analyzes it based off the relationship between the user instead of just simply header information. Through their research they have found that the patterns displayed over time are significant to that persons life. This application is aimed at the end user instead of other sectors of the social network analysis community. Their visualization is comprised of two types of words: yearly and monthly. Yearly words are static and are large an grey, and faint in the background showing the most commonly used words over the year. Monthly words are interactive, yellow, and shown in the foreground as stacks on the timeline of the screen as a space. These words can be selected and interacted with to see the emails they showed in and other contexts. Additionally, there are circles that are exchanged in a month, the size of the circle indicates how lengthy the message was. The main functionalities this application tries to accomplish is to show the user (1) what do I talk about with a specific person in my email and (2) what are the differences in my conversations between people. This was used in user studies and case studies that gave positive feedback on this application, in which most users preferred the overall view (called haystack), instead of the detailed view you get from clicking on each word monthly (called needle). They liked the application to be able to see and remember their interactions with people. Some of the disadvantages to the way this application was created are that it does not differentiate between expressions, it only sees individuals words, limiting its accuracy in portraying an exact relationship in social terms we have learned as humans in society.

Reflection 

I understand why they chose to do the project and that there was positive feedback from users who volunteered to use the software. However, I do not actually see the value this applications brings to society. That might be because email is outdated, if they were to look at my vt email, it would just show the amount of work I have done, and not personal relationships, or travel records at the most. This applied to messenger applications might be interesting, but still I don’t know what value that brings, besides a emotional value. This emotional value of “looking back” is something a lot of companies deal with our online data have seemed to integrate into their applications. Both Facebook and Google Photos have a “rediscover this day” and “friend-aversairy”. Which at times I, as a user, enjoy when its applicable, sometimes they choose people I no longer have a strong connection without or funerals. I think the concept of reflecting on your life is interesting and something that is good for social media applications. I think this being applied to a different messenger might be something I could see more applications for, but honestly, now that the “rediscover this day” has been out a while, it has lost a lot of steam. I no longer share those anymore, I sometimes take a second to smile, or just simply think “oh yeah that happened”. But I don’t see a long term usage or need for an application like this. What value does this bring? Its the same concept that by the time Google Photos came out with “rediscover this day”, I was already over it. Because it doesn’t really add that much value, and multiple interfaces are reminding me of that event or lots of events. I don’t see a user sitting down at the end of every week/month and using this application to review what interactions they had because its not fulfilling an need they have. I see a user maybe every year, or every few years looking back at it, but then why develop this for an user to barely use unless its just for other purposes and other applications within the industry. This application extended and maybe integrated into the already existing thoughts of “rediscovering” a time, a relationship. or a place, might be of some use. I think users like it in the study like, cause I would like it and think its interesting, but not daily use applicable or even weekly or even monthly.

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10/19

Summary

The article dives into a new funding resource that many individuals and enterprises have used to achieve funding goals: crowdfunding. It specifically looks into the Kickstarter website.
After explaining what exactly kickstarted does and how it works, they go into analytical processing of what works create a successful funding vs not successful, in kickstarter if you achieve you goal you get the money, if not, you don’t get the funding money. The main trend they found is the language that was used to describe the campaign was a predictive factor related to the success of the campaign.

 

Some of these persuasive language elements were reciprocity, scarcity, social proof, social identity, relationship (linking) to the host, and authority. Most of these did not come as a surprise if you think about a verbal persuasive argument and what makes that successful: offering someone in return for their donating (reciprocity), giving them a time or product constraint (scarcity), showing that other people are donating(social proof), a feeling of belonging to a group that is donating (social identity), knowing the person and liking them (linking), and expert opinions on product donating for (authority). All of the data gather was from multiple statistical analysis and some other interesting things were find. At a enterprise  level, creating a crowdfund lead to more collaborations between departments creating a concern for a collective group instead of there own self interests.

 

Personal Reflection

The data gathered was quite similar to what I would have predicted if I studied persuasive arguments in a verbal context, which is interesting that it has the same effect online. I am not interesting in crowdfunding and gathering more data on it, but I do find the way words and social behavior online can affect a users decisions to do or not do something interesting. I found that how they analyzed words and their meaning within them would be applicable for an extension to Tweetasaurus, in being able to analyze the context of the sentence or emotion behind it and then offer better suggestions based on this emotion. Additionally, can any of these persuasion techniques be used to help users of Twetasusaurs encouraged to use it for its better purpose than just a thesaurus? Such as, being able to see other’s changing negative words to better word to create this “social” environment of “social proof”.   

 

Questions

How much does the wording matter? This analyzed the meaning of the wording, but say if someone was trying to appeal to someone’s social identity, but they did so in an ineffective way? Is there a way to measure if they users are “trying” be embody these characteristics, but failing?

 

I found it interesting that it brought people together at enterprise level, is there a way to see if there were any other improvements in the workplace?

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Reading Reflection 9/12

Summary

In the paper “Antisocial Behavior in Online Discussions Communities” the focus was on the behavior patterns of users that eventually get banned from communities for posting inappropriate comments, irrelevant issues, and other behavior patterns that do not comply with standard online community conversation norms. The three main questions they were asking were:

(1) When does a user become antisocial – later in community life or from the start?

(2) What role does the community play in encouraging or discouraging antisocial behavior?

(3) Is it possible to identify antisocial users before they are banned?

These questions were imperative for their analysis because these are the fundamental concepts of understanding who a banned user is and how to prevent/identify trolls before they terrorize a community. They focused on three major websites: CNN.com, Breitbart.com, IGN.com in order to gather information that would provide them with enough data to make accurate claims about banned users. Additionally, these sites have the ability to report users, comment and down like posts. They created two groups of users within the community, Future Banned Users (FBUs) and the Never Banned Users (NBUs). These groups emerged not only because this was their focus, but also because language patterns were similar between FBUs and NBUs, this language that FBU’s used were more controversial and words that provoke users. Additionally, the difference between these two groups, their posting habits were also significantly different, with FBU’s there are more posts and more concentrated on a few threads instead of more spread out as a NBU’s post would be. Additionally, there was a trend that FBUs behaviors worsen the more time spent in that community. Furthermore, they indicated that post deletion and post reports were a high indicator of FBU’s, while number of comments and down likes didn’t have such a strong correlation because they serve other purposes. They have determined that within the first 10 post, they can pretty certainly determine what type of user this is.

 

Personal Reflection

Most of what this article confirms, does not surprise me, it just simply confirms suspects I had about members of on online community. What does surprise me is that there were some trends found with individuals where isolation in the community made the behavior worse. I find this interesting because this makes sense, but also, I am curious how many users get off to the wrong foot, feel isolated, and then lash out. Additionally, I am curious about if banned users are already isolated from society or if they are functioning, just not online. If they aren’t function or are, is there a way we can help them to function online?

 

Questions

Are all FBUs acting in a malicious intent or just simply lacking the social skills that NBU’s have or have learned to have? I know they clearly lack the social skills to function in an online community, but does that mean that some who maybe as a mental disorder that affects their social skills can’t use a community because they don’t understand the norms? That isolates them from participating in online communities and probably other social communities to. Which raises the question: Is social media only simply connecting they already connected within society? Those who have learned the norms and know how to participate in a receptive manner to others? Additionally, could that possibly perpetuate more isolation?

 

For example, an individual with autism, enough to function within society, but still noticeable autism. If all of his friends are participating on online communities, do these studies see him as a FBU? Do they get banned for saying inappropriate things? Does that further isolate them from their social community they may have?

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9/7

Summary

The first article “Social Translucence: An approach to Designing Systems that Support Social Processes” focuses more on how exactly social interactions are developed with one another and how this translates to an online version, or at least how they think this should translate to an online version. This paper then relates it to the design of an application called Babble. While the other paper “The Chat Circles Series: Exploration in designing abstract graphical communication interfaces” focuses on the functions of the application called Chat Circles and how this related to interactions physical social realm, but less focus on how exactly those interactions are formed in the physical atmosphere.

 

The main concepts that were focused on in the paper constructing this idea of social translucence was around the concept of how to build a system that allow users to see behaviours and activities of others as we would see in the physical world. The main idea this was based around was the idea of how to define a social interaction and create the conversation that builds social interactions like it does in the physical world. The three main characteristics that define a social interaction are visibility, awareness, and accountability. They use an example of replacing a solid door with a glass door to ensure individuals using the door would think about the people on the outside of the door before opening it expressing these three key main ideas. Representing this interacting in an online medium to create natural conversation by these key factors: activity support, organizational knowledge spaces, conversation visualization, and restructuring. This article talked very little about the actual Babble application specific implementation of said functionality but did express the need for more research in the area to begin to develop a better social medium for conversations. However, it did make an interesting point (that is still relevant today even though this article is from 2000), the systems today create a barrier between people when in fact we should be trying to build technologies to work with the social interactions and behaviour patterns we already use in society instead of new forms on the web.

 

The second article, was basically an in depth synopsis on how the application Circle Chat works. The concept was to build a graphical chat program to “foster social interaction and expressive communication”. Their main focuses on their design included: background space, individual representation, movement implementation, communication channels, and history depiction. One of their reasons for creating a chatting platform with a focus on the graphics of it is that often in the new forms of communication on chatting applications, tone and character are lost in just simply using words between users. In this article, they mention Babble from the other article as being an “abstract graphical interface element supplementing a persistent chat environment”. They represented users with simple 2D objects with colors and their names beside it, circles can shrink and grow as people converse. In later versions, individuals were able to spatially place themselves to express their interest in the person, the algorithm would move them closer the more the talked, but the user had control on how “close” to get to a person, just as we would in the real world.

 

Reflection

I personally found the second article more thought provoking. What exactly would a good interface look like for representing communication that we have in our daily lives? Currently we use systems like Facebook, Imessage, Twitter, etc to communicate, but how can we form different systems that might break some the barriers we are already used to? I think these articles brought up this point basically. I liked the concept of being about to see who is contributing to a chat conversation more easily by just looking at the visual representation. Or who talk to more over chat by how close our circle are. However, I don’t quite know how I feel about placing comments on others like “super funny” because I see potentially group bullying on someone using this tool. Additionally, I don’t know how I feel about having history that was “impressionistic” instead of “factual” I am not sure I would trust, or maybe I would trust it more. This would be interesting to study to see if people actually did trust it more or less.

 

I don’t have any specific research questions from these articles, but they make me think about over concepts of how we currently communicate.

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Reading Reflection 9/5

Summary

The article “Analysis of Anonymity and Ephemerality in a Large Online Community” constructs and analyzes ideas about anonymity and ephemerality on social networks such as 4chan to see what type of community develops with these characteristics. 4chan is a website that threads expire after being at the bottom of the 15th page, and item is moved up when someone replies or comments on it to the first page keeping employing the survival of the fittest strategy to social media. There are no user accounts, but there are mechanisms in place to verify an identity if necessary such as tripcode, but they find that most users do not use any of these mechanisms. Most users stay anonymous but they have found ways to acknowledge their ranking within their system. The main conclusion from this study were that when given the opportunity to be anonymous most users take the options, and more participating due to removal of fear of being rejected by a community.

 

The next article, “Identity and Deception in the Virtual Community” also analyzes the identity within a similar virtual community, however, this article goes into depth on how exactly identify is formed and how identity deception plays out in an online community. This article covers concepts of identity such as shown in account name/id, signatures authors provide for themselves and credentials. These forms of identity are how members find trolls and user’s who have the purpose in mind to deceive others. An interesting topic this article brings up is about voice and language, something I wouldn’t have initially thought of when I think about online identity. This is about verbiage usage in the community, which can be an indicator to individuals if a user is being deceptive. For example, if a user claims to be an “expert at construction”, but then doesn’t seem to know the difference between a nut and a bolt, this is how identity can be challenged by voice and language in an online community.

 

Reflection

Both of these articles brings up the topic about identity in a different way. The first is about how identities are handled in an online community without constructive identities and the second is about identity within a community that does encourage constructive identities. I found it particularly interesting that within the community 4chan there was a way to identify yourself and your ranking within the community to gain credibility. To me this shows an interesting trait of humans, the need for an identity, to be credibly, and our inherent mistrust of others or trust in others. Additionally, they mentioned interesting trends in how a user acts when anonymous. It seemed to lend it self that users are more willing to post when they don’t have an identity associated with it because there is less fear of rejection. I find this interesting because personally if I had posted anonymously and everyone hated my post, it would still hurt my feelings, but I would still be more willing to post it. Additionally, the article mentioned that even when given a way to verify their identity, users’ did user this as creating an identity, but they had other forms of credibility that the site designers did not create for them, but the community did.

 

The second article about deception, I found a bit less intriguing, however the main topic I found interesting was what exactly how members found other members that were being deceptive.

 

Questions

Do online communities that ensure verification of identities including skill set lead users to trust other users more?

 

How does an individual’s language change when they are responsible for the answers?

 

How does an individual’s creativity and participation change when they are anonymous vs when they are not?

 

What indicators do members in a community notice of a fraudulent user and which indicators to they tend to miss more often?

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Reading Reflection 8/31

Naaman, Mor, Jeffrey Boase, Chih-Hui Lai. “Is it really about me? Message Content in Social Awareness Streams.” ACM Digital Library, ACM, dl.acm.org/citation.cfm?id=1718953. Accessed 30 Aug. 2017.

Akshay Java, Xiaodan Song, Tim Finin, Belle Tseng. “Why We Twitter: Understanding Microblogging Usage and Communities”. http://aisl.umbc.edu/resources/369.pdf. Accessed 30 Aug. 2017.

Summary

In “Why we Twitter: Understanding Microblogging Usage and Communities”, the author raises the question of understanding why and how microblogging tools are used. In this paper, the data is analyzed by understanding user intent on Twitter and looking at the construction of social networks in respect to geography. Based on their analysis they found that users had these main intentions: daily chatter, conversations, sharing information, and reporting news. Additionally, they found users had three different main roles in different communities: information source, information searcher, and as a friend. Similar roles were also expressed in “Is it Really About Me? Message Content in Social Awareness Streams”, expressing that there are three types of user activities, “Information seeking, information sharing, and social activities”. However, this paper has a different focus on understanding trends within the messages themselves such as their content and what type of user they are called informers or meinformers. There are more meinformers than informers, but based on friends and follower numbers, informers are more well liked. Both papers help shape an idea that Twitter is a site used for quick expression of an idea, thought, or expression of a feeling, showing user do have a distinct behavior patterns and connections with one another that can be analyzed to see trends.

Reflection

Both of these papers provide an overview of what kind of data and correlations can be found from Tweets, which I find useful for gaining insight into Social Computing in general such as determining types of users, geographical connection between users, and the response of other socially based on types of users. They both came to conclusions about their original questions. However, I think providing options for possible applications for the conclusions could have been beneficial. Despite this, the papers did a good job at creating some further questions for more research based off topics covered in them.

I found the second paper about how users’ who are “me now” focused had less followers than informers, which makes sense, but I often feel the “me now” posted are created for the reason of getting attention from others. The data provided seemed to contradict the individual’s personal goal of receiving more attention, because it inherently makes them less attractive for others to follow. Therefore, it is is interesting to wonder why the individual continues to make “me now” posts if, based off this research, it is not accomplishing the task of bringing in more attention (or friends). Logically, if a user was a machine, it would notice this and switch to the informer role, but as humans, we struggle to reflect on ourselves and behaviours in such a way. This brings some curiosity in my mind on how we portray ourselves on social media in connection with what social media provides for us mentally and emotionally. I am not sure how that could be made quantifiable, but it’s an interesting question to me.

Questions

Some other research questions that I became curious about from these papers were:

Is there any connection to a change in language within a user’s tweeting from recent tweets the user was tagged in, celebrity following, or news following?  

For example: If User A follows Kim Kardashian, and Kim starts using the word “kitties” to express upset, will the user in the future start using that language as a result of following Kim? How much affect is there (if any) or correlation is your social media language based on others such as celebrities?

Do we see a trend that users in America don’t follow other users in foreign countries, but non-Americans follow more Americans? Does this mean the rest of the world is more in touch with American society than Americans are with other societies?

For example: The whole world was watching the last American election, but did American’s care about any other world elections?

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