Abstract

The rise of fake news in the past decade has brought with it a host of consequences, from swaying opinions on elections to generating uncertainty during a pandemic. A majority of methods developed to combat disinformation either focus on fake news content or malicious actors who generate it. However, the virality of fake news is largely dependent upon the users who propagate it. A deeper understanding of these users can contribute to the development of a framework for identifying users who are likely to spread fake news. In this work, we study the characteristics and motivational factors of fake news spreaders on social media with input from psychological theories and behavioral studies. We then perform a series of experiments to determine if fake news spreaders can be found to exhibit different characteristics than other users. Further, we investigate our findings by testing whether the characteristics we observe amongst fake news spreaders in our experiments can be applied to the detection of fake news spreaders in a real social media environment.

Original languageEnglish (US)
Title of host publicationHT 2021 - Proceedings of the 32nd ACM Conference on Hypertext and Social Media
PublisherAssociation for Computing Machinery, Inc
Pages225-230
Number of pages6
ISBN (Electronic)9781450385510
DOIs
StatePublished - Aug 30 2021
Event32nd ACM Conference on Hypertext and Social Media, HT 2021 - Virtual, Online, Ireland
Duration: Aug 30 2021Sep 2 2021

Publication series

NameHT 2021 - Proceedings of the 32nd ACM Conference on Hypertext and Social Media

Conference

Conference32nd ACM Conference on Hypertext and Social Media, HT 2021
Country/TerritoryIreland
CityVirtual, Online
Period8/30/219/2/21

Keywords

  • fake news
  • fake news spreader
  • psychological theories
  • social and behavioral studies
  • social media

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Graphics and Computer-Aided Design
  • Human-Computer Interaction
  • Software

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