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On Modeling Virality of Twitter Content

  • Tuan-Anh Hoang
  • Ee-Peng Lim
  • Palakorn Achananuparp
  • Jing Jiang
  • Feida Zhu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7008)

Abstract

Twitter is a popular microblogging site where users can easily use mobile phones or desktop machines to generate short messages to be shared with others in realtime. Twitter has seen heavy usage in many recent international events including Japan earthquake, Iran election, etc. In such events, many tweets may become viral for different reasons. In this paper, we study the virality of socio-political tweet content in the Singapore’s 2011 general election (GE2011). We collected tweet data generated by about 20K Singapore users from 1 April 2011 till 12 May 2011, and the follow relationships among them. We introduce several quantitative indices for measuring the virality of tweets that are retweeted. Using these indices, we identify the most viral messages in GE2011 as well as the users behind them.

Keywords

Twitter User Viral Content Virality Model Twitter Data Desktop Machine 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Tuan-Anh Hoang
    • 1
  • Ee-Peng Lim
    • 1
  • Palakorn Achananuparp
    • 1
  • Jing Jiang
    • 1
  • Feida Zhu
    • 1
  1. 1.School of Information SystemsSingapore Management UniversitySingapore

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