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

• Main Authors: Reis, Julio C. S, Melo, Philipe, Belém, Fabiano, Murai, Fabricio, Almeida, Jussara M, Benevenuto, Fabricio
• Format: Journal Article
• Language: English
• Published: 28.08.2023
• Subjects: Computer Science - Computers and Society
• DOI: 10.48550/arxiv.2308.14782

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.