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 BenevenutoAuthors Info & Claims
Pages 159 - 167
Abstract
Digital news outlets have largely replaced traditional newspapers and television as the primary channels for information consumption in Brazil, and WhatsApp plays a crucial role in this context, by disseminating specific news stories. The creation of large public chat groups with numerous users and the ease of message forwarding have made the app popular among Brazilians as an affordable and immediate communication alternative. However, this has also put the platform in a central position in spreading misinformation campaigns. The platform’s closed architecture, protected by end-to-end encryption, poses a challenge for investigating and fact-checking WhatsApp content, hampering efforts to combat this problem. 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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Index Terms
- Helping Fact-Checkers Identify Fake News Stories Shared through Images on WhatsApp
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October 2023
285 pages
ISBN:9798400709081
DOI:10.1145/3617023
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Published: 23 October 2023
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WebMedia '23: Brazilian Symposium on Multimedia and the Web
October 23 - 27, 2023
Ribeirão Preto, Brazil
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