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Identifying Users with Opposing Opinions in Twitter Debates

  • Ashwin Rajadesingan
  • Huan Liu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8393)

Abstract

In recent times, social media sites such as Twitter have been extensively used for debating politics and public policies. These debates span millions of tweets and numerous topics of public importance. Thus, it is imperative that this vast trove of data is tapped in order to gain insights into public opinion especially on hotly contested issues such as abortion, gun reforms etc. Thus, in our work, we aim to gauge users’ stance on such topics in Twitter. We propose ReLP, a semi-supervised framework using a retweet-based label propagation algorithm coupled with a supervised classifier to identify users with differing opinions. In particular, our framework is designed such that it can be easily adopted to different domains with little human supervision while still producing excellent accuracy.

Keywords

label propagation semi-supervised opinion mining polarity detection 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Ashwin Rajadesingan
    • 1
  • Huan Liu
    • 1
  1. 1.Arizona State UniversityUSA

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