articleNov 6, 2017GREEN OA

CSI

NRNatali RuchanskySSSungyong SeoYLYan Liu

University of Southern California

Indexed inarxivcrossref

Abstract

The topic of fake news has drawn attention both from the public and the academic communities. Such misinformation has the potential of affecting public opinion, providing an opportunity for malicious parties to manipulate the outcomes of public events such as elections. Because such high stakes are at play, automatically detecting fake news is an important, yet challenging problem that is not yet well understood. Nevertheless, there are three generally agreed upon characteristics of fake news: the text of an article, the user response it receives, and the source users promoting it. Existing work has largely focused on tailoring solutions to one particular characteristic which has limited their success and…

Citation impact

812
total citations
FWCI
99.74
Percentile
100%
References
23
Citations per year

Authors

3
  • NR
    Natali RuchanskyCorresponding

    University of Southern California

  • SS
    Sungyong Seo

    University of Southern California

  • YL
    Yan Liu

    University of Southern California

Topics & keywords

Topics
Keywords
  • Misinformation
  • Key (lock)
  • Fake news
  • Topic model
  • Artificial neural network
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Funding