Controversial topic discovery on members of congress with Twitter

Aleksey Panasyuk, Edmund Szu Li Yu, Kishan G. Mehrotra

Research output: Chapter in Book/Entry/PoemConference contribution

6 Scopus citations


This paper addresses how Twitter can be used for identifying conflict between communities of users. We aggregate documents by topic and by community and perform sentiment analysis, which allows us to analyze the overall opinion of each community about each topic. We rank the topics with opposing views (negative for one community and positive for the other). For illustration of the proposed methodology we chose a problem whose results can be evaluated using news articles. We look at tweets for republican and democrat congress members for the 112th House of Representatives from September to December 2013 and demonstrate that our approach is successful by comparing against articles in the news media.

Original languageEnglish (US)
Title of host publicationProcedia Computer Science
Number of pages8
StatePublished - 2014
EventComplex Adaptive Systems, 2014 - Philadelphia, United States
Duration: Nov 3 2014Nov 5 2014


OtherComplex Adaptive Systems, 2014
Country/TerritoryUnited States


  • Latent dirichlet allocation
  • Polarizing topics
  • Semantic extraction
  • Social media mining
  • Topic modeling
  • Twitter

ASJC Scopus subject areas

  • General Computer Science


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