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AuthorWatheq, Mansour
AuthorElsayed, Tamer
AuthorAl-Ali, Abdulaziz
Available date2023-11-23T07:45:00Z
Publication Date2023-07-31
Publication NameInformation Processing & Management
Identifierhttp://dx.doi.org/10.1016/j.ipm.2023.103414
CitationMansour, W., Elsayed, T., & Al-Ali, A. (2023). This is not new! Spotting previously-verified claims over Twitter. Information Processing & Management, 60(4), 103414.‏
ISSN03064573
URIhttps://www.sciencedirect.com/science/article/pii/S0306457323001516
URIhttp://hdl.handle.net/10576/49619
AbstractSeveral fake claims are commonly repeated over time, especially on social media. To identify such previous claims, the verified claim retrieval task was studied, where, for a given input claim, the goal is to find previously-verified claims that are relevant to it. However, this view assumes that each claim was already verified, which may not be true for all claims in the real-world scenario. In this work, we introduce the Verified Claim Checking problem over Twitter, in which the relevant verified claims are retrieved only if the input claim was indeed previously-verified, thus saving computation time. We address the problem by proposing SpotVC, an end-to-end approach consisting of two stages, namely a filter and a reranker. The proposed filter achieved an average F1 of 0.81 while significantly reducing computation time. Moreover, the proposed reranker outperformed the state-of-the-art models on two public datasets and provided on-par performance on a third one. Overall, our proposed system exhibits an effective operational balance in the trade-off between efficiency and effectiveness for the real-world scenario.
SponsorThis work was made possible by NPRP grant# NPRP11S-1204-170060 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.
Languageen
PublisherElsevier
SubjectVerified claim checking
Fact checking
Fake news detection
Efficiency
Retrieval
Classification
TitleThis is not new! Spotting previously-verified claims over Twitter
TypeArticle
Issue Number4
Volume Number60
Open Access user License http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.accessType Open Access


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