Chair: David Ayman Shamma, Yahoo! Research, USA
Profanity Use in Online Communities
Contribution & Benefit: Exposes poor performance of list-based profanity detection systems through evaluation of systems and failures. Analysis of community differences regarding creation/tolerance of profanity on social news site suggests new approach.
Abstract » As user-generated Web content increases, the amount of inappropriate and/or objectionable content also grows. Several scholarly communities are addressing how to detect and manage such content: research in computer vision focuses on detection of inappropriate images, natural language processing technology has advanced to recognize insults. However, profanity detection systems remain flawed. Current list-based profanity detection systems have two limitations. First, they are easy to circumvent and easily become stale–that is, they cannot adapt to misspellings, abbreviations, and the fast pace of profane slang evolution. Secondly, they offer a one-size fits all solution; they typically do not accommodate domain, community and context specific needs. However, social settings have their own normative behaviors–what is deemed acceptable in one community may not be in another. In this paper, through analysis of comments from a social news site, we provide evidence that current systems are performing poorly and evaluate the cases on which they fail. We then address community differences regarding creation/tolerance of profanity and suggest a shift to more contextually nuanced profanity detection systems.ACM
Consensus Building in Open Source User Interface Design Discussions
Contribution & Benefit: Reports on a study of consensus building in user interface design discussions in open source software. Provides design implications for promoting consensus in distributed discussions of user interface design issues.
Abstract » We report results of a study which examines consensus ACM
building in user interface design discussions in open source
software communities. Our methodology consisted of
conducting interviews with designers and developers from
the Drupal and Ubuntu communities (N=17) and analyzing
a large corpus of interaction data collected from Drupal.
The interviews captured user perspectives on the challenges
of reaching consensus, techniques employed for building
consensus, and the consequences of not reaching consensus.
We analyzed the interaction data to determine how different
elements of the content, process, and user relationships in
the design discussions affect consensus. Our main result
shows that design discussions engaging participants with
more experience and prior interaction history are more
likely to reach consensus. Based on all of our results, we
formulated design implications for promoting consensus in
distributed discussions of user interface design issues.
"I can't get no sleep": Discussing #insomnia on Twitter
Contribution & Benefit: Examines the disclosure of insomnia over twitter, recognising two themes: description of experience, and coping mechanisms. Design implications for social media based mental health interventions are inferred.
Abstract » Emerging research has shown that social media services are being used as tools to disclose a range of personal health information. To explore the role of social media in the discussion of mental health issues, and with particular reference to insomnia and sleep disorders, a corpus of 18,901 messages - or Tweets - posted to the microblogging social media service Twitter were analysed using a mixed methods approach. We present a content analysis which revealed that Tweets that contained the word �insomnia� contained significantly more negative health information than a random sample, strongly suggesting that individuals were making disclosures about their sleep disorder. A subsequent thematic analysis then revealed two themes: coping with insomnia, and describing the experience of insomnia. We discuss these themes as well as the implications of our research for those in the interaction design community interested in integrating online social media systems in health interventions.ACM
Introducing the Ambivalent Socialiser
Contribution & Benefit: Describes four approaches to introduce sociality to people who are simultaneously keen but also reluctant to participate in social media. Can assist designers of persuasive technology to utilise social influence.
Abstract » Social interaction can be a powerful strategy for persuasive technology interventions, yet many users are reluctant to engage with others online because they fear pressure, failure and shame. We introduce the �ambivalent socialiser�, a person who is simultaneously keen but also reluctant to engage with others via social media. Our contribution is to identify four approaches to introducing sociality to ambivalent socialisers: structured socialising, incidental socialising, eavesdropping and trace sensing. We discuss the rationale for these approaches and show how they address recent critiques of persuasive technology. Furthermore, we provide actionable insights for designers of persuasive technology by showing how these approaches can be implemented in a social media application.ACM
Twitter and the Development of an Audience: Those Who Stay on Topic Thrive!
Contribution & Benefit: Describes a longitudinal study examining how initial topical focus influences communities' ability to attract a critical mass. Can assist in understanding the development of online social networking structures.
Abstract » Although economists have long recognized the importance of a critical mass in growing a community, we know little about how it is achieved. This paper examines how initial topical focus influences communities' ability to attract a critical mass. When starting an online community, organizers need to define its initial scope. Topically narrow communities will probably attract a homogeneous group of interested in its content and compatible with each other. However, they are likely to attract fewer members than a diverse one because they offer only a subset of the topics. This paper reports an empirical analysis of longitudinal data collected from Twitter, where each new Twitter poster is considered the seed of a potential social collection. Users who focus the topics of their early tweets more narrowly ultimately attract more followers with more ties among them. Our results shed light on the development of online social networking structures.ACM