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Case Study & Paper

May 10, 2012 @ 11:30, Room: 12AB

Chair: Sadat Shami, IBM Research, USA
Designing Social Translucence Over Social Networks - Paper
Contribution & Benefit: Social translucence is a landmark theory in social computing. However, we argue that it breaks down over modern social network sites and build a theory relating network structure to design.
Abstract » Social translucence is a landmark theory in social computing. Modeled on physical life, it guides designers toward elegant social technologies. However, we argue that it breaks down over modern social network sites because social networks resist its physical metaphors. In this paper, we build theory relating social translucence to social network structure. To explore this idea, we built a tool called Link Different. Link Different addresses a structural awareness problem by letting users know how many of their Twitter followers already a saw link via someone else they follow. During two months on the web, nearly 150K people used the site a total of 1.3M times. Its widespread, viral use suggests that people want social translucence, but network structure gets in the way. We conclude the paper by illustrating new design problems that lie at the intersection of social translucence and other unexplored network structures.
A Longitudinal Study of Facebook, LinkedIn, & Twitter Use - Paper
Community: management
Contribution & Benefit: Our longitudinal study of attitudes and behaviors around popular social networking sites in an enterprise context will contribute to understanding and potentially to design in this dynamic technology area.
Abstract » We conducted four annual comprehensive surveys of social networking at Microsoft between 2008 and 2011. We are interested in how employees use these tools and whether they consider then useful for organizational communication and information-gathering. Our study is longitudinal and based on random sampling. Between 2008 and 2011social networking went from being a niche activity to being very widely and heavily used. Growth in use and acceptance was not uniform, with differences based on gender, age and level (individual contributor vs. manager). Behaviors and concerns changed, with some showing signs of leveling off.
Breaking News on Twitter - Note
Contribution & Benefit: Case study of how Twitter broke and spread the news of Osama Bin Laden's death. Contributes to our understanding of trust and information flow on Twitter.
Abstract » After the news of Osama Bin Laden's death leaked through Twitter, many people wondered if Twitter would fundamentally change the way we produce, spread, and consume news. In this paper we provide an in-depth analysis of how the news broke and spread on Twitter. We confirm the claim that Twitter broke the news first, and find evidence that Twitter had convinced a large number of its audience before mainstream media confirmed the news. We also discover that attention on Twitter was highly concentrated on a small number of "opinion leaders" and identify three groups of opinion leaders who played key roles in spreading the news: individuals affiliated with media played a large part in breaking the news, mass media brought the news to a wider audience and provided eager Twitter users with content on external sites, and celebrities helped to spread the news and stimulate conversation. Our findings suggest Twitter has great potential as a news medium.
The Twitter Mute Button: A Web Filtering Challenge - Note
Community: user experience
Contribution & Benefit: We describe the challenge of selectively filtering Twitter content and illustrate this through a pilot study on filtering spoilers posted about televised events.
Abstract » The microblogging service Twitter has become an important, and sometimes primary, source of information for many users. As a forum for sharing news and discussing events, it can provide instant access to the latest updates, but this is not always welcome. In the case of television shows or live sporting events, for example, tweets about them may reveal spoilers to users in different time zones or who are delaying their viewing until later. More broadly, because Twitter is a broadcast medium, users may often want to temporarily or permanently hide content about a very specific given topic.

In this paper, we describe the unique challenges to HCI, social computing, and computational linguistics posed by the task of building an interface that blocks all tweets about a specific event or topic. We illustrate some of the challenges through a pilot experiment run for three major television events: the 2009 NFC Championship football game, the 2010 mid-season finale of the show Glee, and the 2010 season premiere of the show 24. While simple techniques achieve very high recall (>98%), spoilers still make it through the filter and precision is extremely poor. We conclude with a description of challenges to the community in implementing this new and increasingly important feature.
Nokia Internet Pulse: A Long Term Deployment and Iteration of a Twitter Visualization - Long Case Study
Community: design
Contribution & Benefit: This case study discusses the iterative design of a corporate system for visualizing tweets, showing sentiment and word frequency in an ambient display of current and recent public discussion.
Abstract » Nokia Internet Pulse is a system for visualizing current discussion around a particular topic on Twitter. It consists of a time-series of stacked tag clouds consisting of the (interesting) words in tweets that match a topic. Words are sized proportional to frequency and colored according to the emotional content of the tweet: if several people tweet 'I love my Nokia N900', then 'N900' will show up colored bright green, because it's in the same tweet as the word 'love', which the system recognizes as positive. In addition to showing topics of corporate interest ('Nokia', 'N9', etc.), the system is also useful for understanding buzz around individuals ('Rihanna'), conferences ('#chi2012'), topics ('rumor OR rumors'), Twitter-specific phenomena ('RT') and more. Clicking on words shows a list of tweets that contain those words, allowing easy drill-down to view individual tweets. It is available at