Display options
Share it on

Front Psychol. 2018 Feb 21;9:189. doi: 10.3389/fpsyg.2018.00189. eCollection 2018.

Topic Modeling Reveals Distinct Interests within an Online Conspiracy Forum.

Frontiers in psychology

Colin Klein, Peter Clutton, Vince Polito

Affiliations

  1. School of Philosophy, The Australian National University, Canberra, ACT, Australia.
  2. ARC Centre of Excellence in Cognition and its Disorders, Macquarie University, Sydney, NSW, Australia.
  3. Department of Cognitive Science, Macquarie University, Sydney, NSW, Australia.

PMID: 29515501 PMCID: PMC5826393 DOI: 10.3389/fpsyg.2018.00189

Abstract

Conspiracy theories play a troubling role in political discourse. Online forums provide a valuable window into everyday conspiracy theorizing, and can give a clue to the motivations and interests of those who post in such forums. Yet this online activity can be difficult to quantify and study. We describe a unique approach to studying online conspiracy theorists which used non-negative matrix factorization to create a topic model of authors' contributions to the main conspiracy forum on Reddit.com. This subreddit provides a large corpus of comments which spans many years and numerous authors. We show that within the forum, there are multiple sub-populations distinguishable by their loadings on different topics in the model. Further, we argue, these differences are interpretable as differences in background beliefs and motivations. The diversity of the distinct subgroups places constraints on theories of what generates conspiracy theorizing. We argue that traditional "monological" believers are only the tip of an iceberg of commenters. Neither simple irrationality nor common preoccupations can account for the observed diversity. Instead, we suggest, those who endorse conspiracies seem to be primarily brought together by epistemological concerns, and that these central concerns link an otherwise heterogenous group of individuals.

Keywords: conspiracies; conspiracy theorists; reddit; social media; topic models

References

  1. Proc Natl Acad Sci U S A. 2016 Jan 19;113(3):554-9 - PubMed
  2. J Med Internet Res. 2015 Jun 10;17(6):e144 - PubMed
  3. Nature. 1999 Oct 21;401(6755):788-91 - PubMed
  4. Front Psychol. 2015 Jun 17;6:836 - PubMed
  5. Front Psychol. 2013 Jul 09;4:406 - PubMed
  6. Stud Health Technol Inform. 2015 ;216:761-5 - PubMed
  7. Front Psychol. 2015 Feb 25;6:206 - PubMed
  8. Br J Psychol. 2011 Aug;102(3):443-63 - PubMed
  9. Science. 2008 Oct 3;322(5898):115-7 - PubMed
  10. Proc SIGCHI Conf Hum Factor Comput Syst. 2016 May;2016:2098-2110 - PubMed
  11. Cognition. 2014 Dec;133(3):572-85 - PubMed
  12. PLoS One. 2015 Aug 14;10(8):e0134641 - PubMed
  13. Psychol Sci. 2013 May;24(5):622-33 - PubMed

Publication Types