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arXiv · 2308.14782

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

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.

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Julio C. S. Reis, Philipe Melo, Fabiano Belém, Fabricio Murai, Jussara M. Almeida, Fabricio Benevenuto. 2023-08-28. Helping Fact-Checkers Identify Fake News Stories Shared through Images on WhatsApp. https://arxiv.org/abs/2308.14782

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