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“This is Fake! Shared it by Mistake”: Assessing the Intent of Fake News Spreaders

  • Xinyi Zhou
  • , Kai Shu
  • , Vir V. Phoha
  • , Huan Liu
  • , Reza Zafarani
  • Syracuse University
  • Illinois Institute of Technology
  • Arizona State University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

36 Scopus citations

Abstract

Individuals can be misled by fake news and spread it unintentionally without knowing it is false. This phenomenon has been frequently observed but has not been investigated. Our aim in this work is to assess the intent of fake news spreaders. To distinguish between intentional versus unintentional spreading, we study the psychological explanations of unintentional spreading. With this foundation, we then propose an influence graph, using which we assess the intent of fake news spreaders. Our extensive experiments show that the assessed intent can help significantly differentiate between intentional and unintentional fake news spreaders. Furthermore, the estimated intent can significantly improve the current techniques that detect fake news. To our best knowledge, this is the first work to model individuals’ intent in fake news spreading.
Original languageAmerican English
Title of host publicationProceedings of the ACM Web Conference 2022
Place of PublicationNew York, NY, USA
PublisherAssociation for Computing Machinery
Pages3685–3694
Number of pages10
ISBN (Print)9781450390965
DOIs
StatePublished - 2022
Externally publishedYes

Publication series

NameWWW '22
PublisherAssociation for Computing Machinery

Keywords

  • Fake news
  • intent
  • social media

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