Twitter zombie: architecture for capturing, socially transforming and analyzing the twittersphere

ABSTRACT

Social computational systems emerge in the wild on popular social networking sites like Facebook and Twitter, but there remains confusion about the relationship between social interactions and the technical traces of interaction left behind through use. Twitter interactions and social experience are particularly challenging to make sense of because of the wide range of tools used to access Twitter (text message, website, iPhone, TweetDeck and others), and the emergent set of practices for annotating message context (hashtags, reply to's and direct messaging). Further, Twitter is used as a back channel of communication in a wide range of contexts, ranging from disaster relief to watching television. Our study examines Twitter as a transport protocol that is used differently in different socio-technical contexts, and presents an analysis of how researchers might begin to approach studies of Twitter interactions with a more reflexive stance toward the application programming interfaces (APIs) Twitter provides. We conduct a careful review of existing literature examining socio-technical phenomena on Twitter, revealing a collective inconsistency in the description of data gathering and analysis methods. In this paper, we present a candidate architecture and methodological approach for examining specific parts of the Twittersphere. Our contribution begins a discussion among social media researchers on the topic of how to systematically and consistently make sense of the social phenomena that emerge through Twitter. This work supports the comparative analysis of Twitter studies and the development of social media theories.

References

1. mments and Retweets: Facebooking and Tweeting on the 2010 Gubernatorial Campaign Trail. State Politics and Policy Conference. 11th.
2. Quercia, D., Ellis, J., Capra, L., and Crowcroft, J. 2012. Tracking "Gross Community Happiness" from Tweets. CSCW.
3. Romero, D. M., Meeder, B., and Kleinberg, J. 2011. Differences in the Mechanics of Information Diffusion Across Topics: Idioms, Political Hashtags, and Complex Contation on Twitter. WWW.
4. Starbird, K., Palen, L., Hughes, A. L., and Vieweg, S. 2010. Chatter on The Red: What Hazards Threat Reveals about the Social Life of Microblogged Information. CSCW.
5. Sutton, J., Palen, L., and Shklovski, I. 2008. Backchannels on the front lines: Emergent use of social media in the 2007 Southern California fire. Information Systems for Crisis Response and Management Conference.
6. Tumasjan, A., Sprenger, T. O., Sandner, P. G., and Welpe, I. M. 2010. Predicting Elections with Twitter: What 140 Characters Reveal about Political Sentiment. ICWSM. 4th.
7. Werry, C. C. 1996 Linguistic and interactional features of Internet Relay Chat. In Computer-mediated communication: Linguistic, social and cross-cultural perspectives, S. C. Herring,Ed John Benjamins.
8. Williams, C. and Gulati, G. J. 2008. What is a Social Network Worth? Facebook and Vote Share in the 2008 Presidential Primaries. American Political Science Association.
9. Wohn, D. Y. and Na, E. K. 2011. Tweeting about TV: Sharing television viewing experiences via social media message streams. First Monday. 16, 3.
10. Zelenkauskaite, A. and Herring, S. C. 2008. Television-mediated conversation: Coherence in Italian iTV SMS Chat. Hawaii International Conference on System Sciences. 41.
11. Zhao, S., Zhong, L., Wickramasuriya, J., and Vasudevan, V. 2011. Human as Real-Time Sensors of Social and Physical Events: A Case Study of Twitter and Sports Games. rxiv preprint arXiv:1106.4300.

Index Terms

• Human-centered computing

  • Collaborative and social computing

• Software and its engineering

  • Software notations and tools

    • General programming languages

      • Language features

        • Data types and structures