Example of targeting for the claim Report: three million votes in presidential election cast by illegal aliens, published by Infowars.com on November 14, 2016 and shared over 18 thousand times on Twitter. Only a portion of the diffusion network is shown. Nodes stand for Twitter accounts, with size representing number of followers. Links illustrate how the claim spreads: by retweets and quoted tweets (blue), or by replies and mentions (red).

The Spread of Fake News by Social Bots

Abstract

The massive spread of fake news has been identified as a major global risk and has been alleged to influence elections and threaten democracies. Communication, cognitive, social, and computer scientists are engaged in efforts to study the complex causes for the viral diffusion of digital misinformation and to develop solutions, while search and social media platforms are beginning to deploy countermeasures. However, to date, these efforts have been mainly informed by anecdotal evidence rather than systematic data. Here we analyze 14 million messages spreading 400 thousand claims on Twitter during and following the 2016 U.S. presidential campaign and election. We find evidence that social bots play a key role in the spread of fake news. Accounts that actively spread misinformation are significantly more likely to be bots. Automated accounts are particularly active in the early spreading phases of viral claims, and tend to target influential users. Humans are vulnerable to this manipulation, retweeting bots who post false news. Successful sources of false and biased claims are heavily supported by social bots. These results suggest that curbing social bots may be an effective strategy for mitigating the spread of online misinformation.

Publication
arXiv preprint arXiv:1707.07592
Date
Links

BibTeX

@Article{Shao2017,
  Title                    = {The spread of fake news by social bots},
  Author                   = {Shao, Chengcheng and Ciampaglia, Giovanni Luca and Varol, Onur and Flammini, Alessandro and Menczer, Filippo},
  Journal                  = {ArXiv e-prints},
  Year                     = {2017},

  Month                    = jul,

  Archiveprefix            = {arXiv},
  Eprint                   = {1707.07592},
  Primaryclass             = {cs.SI}
}