Summary

In “Visualizing Email Content: Portraying Relationships from Conversational Histories,” the authors Viegas, Golder, and Donath describe relationships between individuals over email. Themail, the interface created that shows these interactions and relationships, displays words pulled from emails. These words are categorized via a yearly or monthly basis; yearly words portray the overall tone of relationship, whereas monthly emails are more detailed. On the interface of the application, yearly words are displayed in the background in light gray, and monthly words are yellow in the foreground. When a specific word is selected, emails that contain the word appear. In order to test Themail, a study was provided such that participants could use one of two modes: the haystack mode or the needle mode. The haystack mode allowed users to view an overall picture of the relationships they had over email. Over the course of the study, a majority of the users (about 80%) decided to use the haystack mode because they wanted to see their relationships with their family and friends and confirm their expectations with their findings. On the other hand, the needle mode allowed users to view specific pieces of data to identify patterns in their relationships. The other 20% of the population were more concerned with analyzing their workplace relationships rather than those with their friends and family. The authors also discuss how most users would not utilize this application daily, rather, it is more probable that users use Themail every so often.

Reflection

Something I found interesting was the difference between the haystack and needle mode users. In the description of the the needle mode, the paper discusses that haystack users wanted to see information they already knew, but the needle users wanted to determine information they didn’t know or couldn’t remember. In particular, the authors note that about 20% of users used the needle mode, which made me curious if all the users only utilized Themail for one sole purpose (i.e. only haystack or only needle). Additionally, it was intriguing how the range of email archives ranged from 90 MB to more than 1GB with an average of 456 MB because I know that there extremes to people who email – some delete all their emails, and some don’t delete at all. For those who delete all their emails, Themail would obviously not be as applicable of an application. I actually don’t ever clean out or delete my emails, so I probably have a lot of data to sort through; however, I don’t think fruitful information pertaining my personal relationships would appear. This is especially because in this day and age most people don’t communicate solely over email. It would be interesting to apply this to texts.

Questions

• Though they would likely vary from person to person, which words were most popularly used?
• How could the UI change to make it less cluttered and perhaps easier to read?
• Is there a significance to placing the yearly words in the background rather than just displaying them on the side (or elsewhere in a different manner)?

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Summary

“The Language that Gets People to Give: Phrases that Predict Success on Kickstarter” discusses the factors that allow Kickstarter projects to be funded by a “crowd.” Kickstarter is a crowd funding website where backers (users in the “crowd”) can fund a project in order to help the project achieve its goal. If the goal is achieved, the project or product will be created, else the project fails and the money is returned to the backers. The major attributes that help projects be funded include project duration, goal amount, language, and video present/length. In particular, the authors discuss the language that project creators can use to engage backers, which was determined via scraping data from a sample of Kickstarter projects, such as project description and reward details. The phrases found were then analyzed with LIWC in order to categorize the types of words found. Differences between the phrases used in funded and nonfunded projects were observed, and the following categories were established:

1. Reciprocity: returning a favor after receiving one
2. Scarcity: emphasizing that the product is limited (quantity or duration)
3. Social proof: emphasizing that many other people have done xyz, which increases the likelihood of others following and doing the same
4. Social identity: emphasizing that the user is part of the community
5. Liking: complying with a person/product if the user likes them; liking is increased when positive comments are explicitly given about the person/product
6. Authority: including expert-given opinions

It was also found that characteristics of the funded projects include cognitive thinking, social process, perception rates, emotion, and personal concerns. The authors suggest creating an FAQ or Help Center that gives creators tips on having a successfully funded project (although use of the phrases may not guarantee success).

Reflection

I found this paper really interesting because I’ve participated in a Kickstarter project before (for a product that definitely is not too cheap) and the factors that made me interested were:

1. Reciprocity: backers receive the product if they help fund the project
2. Scarcity: backers receive the product at a discount (which is only given to backers) for a limited time
3. Social proof: there were so many other backers for the project

I’m sure this has been done before, but I think it would be really interesting to apply this to clickbait (articles, Youtube videos, etc.) to see if there are specific phrases that make people read them. I think it would be a little difficult to categorize phrases involved in clickbait, however, because it seems that article titles and Youtube video titles can vary more vastly than phrases used in Kickstarter projects (though I could be wrong), and also because titles are much shorter than the data scraped from Kickstarter projects. In this case, I think that clickbait is more dependent on categories of specific words or adjectives rather than whole phrases (which could be determined via LIWC). Nevertheless, it would be intriguing to see which categories these words would fall under.

Questions

• Would an analysis on other crowd funding sites (e.g. gofundme) result in the same results?
• How many phrases in the funded and nonfunded categories overlapped?

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Summary

In “Antisocial Behavior in Online Discussion Communities,” the authors analyze and characterize antisocial behavior of users over time in three online discussion communities, CNN, Breitbart, and IGN. Users of these communities are distinguished into two categories – being banned (Future-Banned Users, FBUs) and never being banned (Never-Banned Users, NBUs). The characteristics that differentiate FBUs from NBUs include using more profanity and less positive words, writing in concentrated individual threads, writing harder to understand posts, and posting less similarly like other users. By comparing posts written by FBUs and NBUs, it was found that the way FBUs are more likely to get off-topic and write posts that appear to be less readable. Similarly, it was made evident that FBUs are effective at engaging other users in irrelevant conversations. Another question the paper addresses is “how do FBUs and their effect on the community change over time?” Through a study of FBUs posts over 17 months, the authors determined that text quality of posts by FBUs decrease, but do not by NBUs. FBUs also became less tolerated by the community over time, and were banned from posting in threads. In order to identify antisocial users before they become FBUs,  Cheng, Danescu-Niculescu-Mizil, and Leskovec establish four features – post readability, user activity, interaction with the community, and moderator involvement.

Reflection

I found the passages about the effects of FBUs on the community interesting because not only do FBUs have a negative effect on the community, the communities also do on FUBs. As the authors state in the paper, “communities play a part in incubating antisocial behavior,” which is definitely true. For instance, communities have a part in creating FBUs by excessively censoring them and having negative reactions to their posts (though in many cases, it may be for good reason). Furthermore, communities also foster antisocial behavior by reacting to FBUs posts, which then can lead to further provocations by FBUs and arguments between the parties. From first hand experience, I think we all know it’s difficult to not respond to a comment that offends us or promotes an opposing viewpoint. I suppose that’s a good reason as to why discussion communities include downvoting – users don’t need to verbally express their disapproval of a post.

Questions

• What makes FBUs want to continue writing harmful/fruitless posts in discussions?
• Since there are methods to detects FBUs, are there ways to help potential FBUs remain as NBUs?
• How fast do moderators delete posts?

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Summary

“Social Translucence: An Approach to Designing Systems that Support Social Processes” discusses the design of interfaces that support meaningful communication on a large scale. Erickson and Kellogg describe the importance of social translucence – characterized by visibility, awareness, and translucence – in digital systems that allow users to enrich their social experiences. Social translucence allows interactions of online users to mimic physical interactions in the real world by following three design approaches: realist, mimetic, and abstract. Decisions users make are dependent on their environment, which is why awareness and visibility of other users is important to incorporate in the design of an online social platform.

In “The Chat Circle Series: Explorations in designing abstract graphical communication interfaces,” authors Donath and Viegas explore the design behind the interfaces of graphical chat programs using Chat Circles. These Chat Circles are a minimalist design environment (using shapes, text, colors, and images) that are influenced by environment, communication channel, individual representation, history, movement, and context. Furthermore, Chat Circles can reveal information such as how frequent users post, what times they post, popular topics of discussion, ambiance of a conversation or topic, and user movement throughout chats.

Reflection

The details of “Social Translucence” about social awareness and the environment that we are in was something I never thought about because though I often communicate online, I do so without much thought to the design of the platform itself. In hindsight, the environment we communicate in does definitely play a large part in how we communicate. For instance, on Instagram, Twitter , and Facebook, we create the environment we are a part of by friending, following, and chatting with certain people that we choose. Updating your status via images or text can also support group awareness; your friends and family are curious as to what you’re doing or what you did. Introducing physical interactions to online interactions was also a fascinating concept to me because obviously aspects of communication such as body language aren’t evident online, but voice and language (as discussed in our previous readings) are and do affect the conversations. Other than body language, voice, and language, other indications of our emotions include emojis, gifs, and stickers.

“The Chat Circle Series” offered an interesting insight on chat interfaces and their design. One feature of Chat Circles I found intriguing is behavioral representations of users on ChatScape using shapes. The particular feature that surprised me the most is the dependency of the user’s shape on the judgement of other participants. For instance, if a user is aggressive or obnoxious (visually, a shape with many edges and angles), would other users want to engage in conversation with them? It is possible that this alter the way users converse because they are more aware of what other participants think of them. The Chat Circles history interface was also cool because it’s very similar to message logs we have today (texts, iMessage, Facebook Messenger), but it displays the posts as horizontal bars. I liked how the history allowed for a visual representation of the frequency and time of posts.

Questions

• In what ways do current social media sites impose walls between people? (I understand the issues the authors pose in the Introduction about digital tools being primitive and cumbersome, but I’m not entirely sure how these impose walls)
• Does a user with more edges on their shape (for ChatScape) make them less approachable?
• Was it fruitful to include behavioral representations on ChatScape?

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Summary

In “Identity and Deception in the Virtual Community,” Judith Donath describes how identity is established in virtual communities, and how identity can be ambiguous due to deception. Donath uses a study on Usenet, a newsgroup in which users can post about specified topics. Key indications of identification include account name, email domain, identity in writing style (voice/language), and signature. Although users are assumed to be who they say they are, these forms of identification can easily be easily faked and used to deceive other users. Categories of deception include trolls, impersonation, and identity concealment. Additionally, the balance between privacy, credibility, and self-expression has still not been “perfected,” such that a community can feel secure about the information they post (or read).

“4chan and /b/: An Analysis of Anonymity and Ephemerality in a Large Online Community” details the effects of anonymity and ephemerality in online communities, in particular 4chan’s /b/ discussion board. On 4chan, posts get pushed off the first page by newer posts, and remain on the top of the first page if the post is popular (has users actively replying). It was found that most posts have short lifespans – 3.9 minutes on average – which displays the fast pace of the /b/ board. 90% of users on /b/ were found to be anonymous, which is suggested to be because it allows for more intimate and open conversation, and new ideas.

Reflection

In the first paper, I found it particularly interesting that email domain was an indication of credibility. Since I typically don’t use websites that rely on the email domain for a user account, I never considered that it would be something that users look at to determine if someone is a reliable source of information. This reminded me of checking top-level domains of websites (.org, .com, .net) when checking sources for research or essays, which is something I and many other students do more often. In this section, Donath uses various examples of prejudice based on email domain – being a “loser” for having an AOL domain, not having “BIG $$$” because of a specific neighborhood/location – which made me think about social media sites that are popular today and why they don’t have usernames based on email.

In “4chan” it was intriguing to me how ephemerality is even a concept because, like email domain, it wasn’t something I ever considered even though it is apparent in social media that I use often (Snapchat, Twitter, etc.). It was interesting especially how ephemerality is affected by time of day, and that threads lasted the longest between 9-10am EST and lasted the shortest between 5-7pm EST due to activity by North American users after work/school. This reminded me of a discussion I had with a friend a year (more or less) ago about when the best time to post a photo on Instagram. This was when Instagram still displayed posts chronologically, and the best time apparently also was around 5-8pm EST since users were getting off from work/school.

Questions

• Will there ever be a balance between privacy, credibility, and self-expression?
• What do people think they gain from harmful forms of deception (catfishing/impersonation, trolling)?
• Why do recent/popular social media sites use username rather than email?
• Does using email as a form of identification on Usenet have more benefits (e.g. allows for credibility) than disadvantages (e.g. bullying)?
• Can current writing styles be categorized to determine reliability?
• Why do websites like Tumblr/Ask.fm still allow anonymity when asking questions?
• Do people enjoy the ephemerality of 4chan and other sites? Why?

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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

“Why We Twitter: Understanding Microblogging Usage and Communities” discusses the use of Twitter as a popular microblogging website and the intent of use by its users. The paper addresses the utilization of blogs to “share daily experiences, opinions, and commentary.” In the past several years, the shift in popularity from blogs to microblogs has become evident. This is due to the convenience of microblogs – each microblog is typically less than 200 characters, thus users are able to spend less time and use less effort to write a post.

In order to determine the intent of users to use Twitter as a microblogging service, an analysis of aggregate behavior of users was performed. Using a HITS algorithm to determine hubs and authorities, communities and relationships were used to categorize intentions and types of users  as follows: information sharing (a source), information seeking (a seeker), and friendship-wise relationship (friends). Furthermore, these intentions could be described as daily chatter, conversations, sharing information, and reporting news. The authors also examine relationships between users, mainly that of mutual following (a bidirectional link where two users “follow” each other). This link displays that communities are built based on interests that are shared between users.

Reflection

This paper describes the concept of microblogging and answers the question of “Why do people use Twitter?” well. The details and description of blogging versus microblogging I found very compelling because I’ve used both tools before; in the past I had used blogging sites such as WordPress and Tumblr, but have grown to enjoy Twitter more due to the brevity of each post. I also found it intriguing how the conclusions of this paper (the three main intentions addressed above) can possibly be considered “obvious” to current users of Twitter in 2017 – we use Twitter to communicate with friends, to share information about our lives, to seek information in the world, etc. This is likely due to the increase in momentum of Twitter since the paper was written (i.e. Twitter has evolved and had an increase in its number of users since it has been available for 11 years as a microblog tool). Additionally, I think it would be interesting to perform another study on Twitter today to see if microblogging intentions are the same or different ten years later.

Questions

• Why is the user’s geographic location important? Is there a correlation between a user’s location and their intent to microblog?
• Do users of a certain geographic locations tweet more about specific topics than others? What topics and why?
• Why at the time was Twitter popular mainly popular in the U.S., Europe, and Asia? Also, why specifically New York, San Francisco, and Japan?
• Since this paper was written, have the main intentions of users changed?

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