Detecting communities by sentiment analysis of controversial topics

Kangwon Seo, Rong Pan, Aleksey Panasyuk

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Controversial topics, particularly political topics, often provoke very different emotions among different communities. By detecting and analyzing communities formed around these controversial topics we can paint a picture of how polarized a country is and how these communities evolved over time. In this research, we made use of Internet data from Twitter, one of the most popular online social media sites, to identify a controversial topic of interest and the emotions expressed towards the topic. Communities were formed based on Twitter users’ sentiments towards the topic. In addition, the network structure of these communities was utilized to reveal those Twitter users that played important roles in their respective communities.

Original languageEnglish (US)
Title of host publicationSocial, Cultural, and Behavioral Modeling - 9th International Conference, SBP-BRiMS 2016, Proceedings
PublisherSpringer Verlag
Pages206-215
Number of pages10
Volume9708
ISBN (Print)9783319399300
DOIs
StatePublished - 2016
Event9th International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction and Behavior Representation in Modeling and Simulation, SBP-BRiMS 2016 - Washington, United States
Duration: Jun 28 2016Jul 1 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9708
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other9th International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction and Behavior Representation in Modeling and Simulation, SBP-BRiMS 2016
CountryUnited States
CityWashington
Period6/28/167/1/16

Keywords

  • Sentiment analysis
  • Social network analysis
  • Topic modeling
  • Twitter

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Seo, K., Pan, R., & Panasyuk, A. (2016). Detecting communities by sentiment analysis of controversial topics. In Social, Cultural, and Behavioral Modeling - 9th International Conference, SBP-BRiMS 2016, Proceedings (Vol. 9708, pp. 206-215). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9708). Springer Verlag. https://doi.org/10.1007/978-3-319-39931-7_20