Quantifying controversy in social media

Kiran Garimella, Gianmarco Morales, Aristides Gionis, Michael Mathioudakis

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

59 Citations (Scopus)

Abstract

Which topics spark the most heated debates in social media? Identifying these topics is a first step towards creating systems which pierce echo chambers. In this paper, we perform a systematic methodological study of controversy detection using social media network structure and content. Unlike previous work, rather than identifying controversy in a single hand-picked topic and use domain-specific knowledge, we focus on comparing topics in any domain. Our approach to quantifying controversy is a graph-based three-stage pipeline, which involves (i) building a conversation graph about a topic, which represents alignment of opinion among users; (ii) partitioning the conversation graph to identify potential sides of the controversy; and (iii) measuring the amount of controversy from characteristics of the graph. We perform an extensive comparison of controversy measures, as well as graph building approaches and data sources. We use both controversial and non-controversial topics on Twitter, as well as other external datasets. We find that our new random-walk-based measure outperforms existing ones in capturing the intuitive notion of controversy, and show that content features are vastly less helpful in this task.

Original languageEnglish
Title of host publicationWSDM 2016 - Proceedings of the 9th ACM International Conference on Web Search and Data Mining
PublisherAssociation for Computing Machinery, Inc
Pages33-42
Number of pages10
ISBN (Electronic)9781450337168
DOIs
Publication statusPublished - 8 Feb 2016
Externally publishedYes
Event9th ACM International Conference on Web Search and Data Mining, WSDM 2016 - San Francisco, United States
Duration: 22 Feb 201625 Feb 2016

Other

Other9th ACM International Conference on Web Search and Data Mining, WSDM 2016
CountryUnited States
CitySan Francisco
Period22/2/1625/2/16

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ASJC Scopus subject areas

  • Computer Science Applications
  • Software
  • Computer Networks and Communications

Cite this

Garimella, K., Morales, G., Gionis, A., & Mathioudakis, M. (2016). Quantifying controversy in social media. In WSDM 2016 - Proceedings of the 9th ACM International Conference on Web Search and Data Mining (pp. 33-42). Association for Computing Machinery, Inc. https://doi.org/10.1145/2835776.2835792