[2305.07796] aedFaCT: Scientific Fact-Checking Made Easier via Semi-Automatic Discovery of Relevant Expert Opinions
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Computer Science > Information Retrieval

arXiv:2305.07796 (cs)
[Submitted on 12 May 2023]

Title:aedFaCT: Scientific Fact-Checking Made Easier via Semi-Automatic Discovery of Relevant Expert Opinions

Authors:Enes Altuncu, Jason R.C. Nurse, Meryem Bagriacik, Sophie Kaleba, Haiyue Yuan, Lisa Bonheme, Shujun Li
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Abstract:In this highly digitised world, fake news is a challenging problem that can cause serious harm to society. Considering how fast fake news can spread, automated methods, tools and services for assisting users to do fact-checking (i.e., fake news detection) become necessary and helpful, for both professionals, such as journalists and researchers, and the general public such as news readers. Experts, especially researchers, play an essential role in informing people about truth and facts, which makes them a good proxy for non-experts to detect fake news by checking relevant expert opinions and comments. Therefore, in this paper, we present aedFaCT, a web browser extension that can help professionals and news readers perform fact-checking via the automatic discovery of expert opinions relevant to the news of concern via shared keywords. Our initial evaluation with three independent testers (who did not participate in the development of the extension) indicated that aedFaCT can provide a faster experience to its users compared with traditional fact-checking practices based on manual online searches, without degrading the quality of retrieved evidence for fact-checking. The source code of aedFaCT is publicly available at this https URL.
Comments: Accepted for publication in the Proceedings of the Workshop on News Media and Computational Journalism (MEDIATE '23), co-located with the AAAI International Conference on Web and Social Media (ICWSM '23)
Subjects: Information Retrieval (cs.IR)
Cite as: arXiv:2305.07796 [cs.IR]
  (or arXiv:2305.07796v1 [cs.IR] for this version)
  https://doi.org/10.48550/arXiv.2305.07796
Journal reference: Workshop Proceedings of the 17th International AAAI Conference on Web and Social Media (2023) 1-10
Related DOI: https://doi.org/10.36190/2023.27

Submission history

From: Enes Altuncu [view email]
[v1] Fri, 12 May 2023 23:09:26 UTC (851 KB)
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