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Computer Science > Computers and Society

arXiv:2308.14782 (cs)
[Submitted on 28 Aug 2023]

Title:Helping Fact-Checkers Identify Fake News Stories Shared through Images on WhatsApp

Authors:Julio C. S. Reis, Philipe Melo, Fabiano Belém, Fabricio Murai, Jussara M. Almeida, Fabricio Benevenuto
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Abstract:WhatsApp has introduced a novel avenue for smartphone users to engage with and disseminate news stories. The convenience of forming interest-based groups and seamlessly sharing content has rendered WhatsApp susceptible to the exploitation of misinformation campaigns. While the process of fact-checking remains a potent tool in identifying fabricated news, its efficacy falters in the face of the unprecedented deluge of information generated on the Internet today. In this work, we explore automatic ranking-based strategies to propose a "fakeness score" model as a means to help fact-checking agencies identify fake news stories shared through images on WhatsApp. Based on the results, we design a tool and integrate it into a real system that has been used extensively for monitoring content during the 2018 Brazilian general election. Our experimental evaluation shows that this tool can reduce by up to 40% the amount of effort required to identify 80% of the fake news in the data when compared to current mechanisms practiced by the fact-checking agencies for the selection of news stories to be checked.
Comments: This is a preprint version of an accepted manuscript on the Brazilian Symposium on Multimedia and the Web (WebMedia). Please, consider to cite it instead of this one
Subjects: Computers and Society (cs.CY)
Cite as: arXiv:2308.14782 [cs.CY]
  (or arXiv:2308.14782v1 [cs.CY] for this version)
  https://doi.org/10.48550/arXiv.2308.14782

Submission history

From: Julio C. S. Reis [view email]
[v1] Mon, 28 Aug 2023 16:12:29 UTC (3,126 KB)
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