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AuthorMansour, Watheq
AuthorElsayed, Tamer
AuthorAl-Ali, Abdulaziz
Available date2023-11-23T11:30:54Z
Publication Date2022-01-01
Publication NameEuropean Conference on Information Retrieval
Identifierhttp://dx.doi.org/10.1007/978-3-030-99736-6_25
CitationMansour, W., Elsayed, T., & Al-Ali, A. (2022, April). Did i see it before? detecting previously-checked claims over twitter. In European conference on information retrieval (pp. 367-381). Cham: Springer International Publishing.‏
ISBN9783030997359
ISSN03029743
URIhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85128789265&origin=inward
URIhttp://hdl.handle.net/10576/49637
AbstractWith the proliferation of fake news in the last few years, especially during the COVID-19 period, combating the spread of misinformation has become an urgent need. Although automated fact-checking systems were proposed recently, they leave much to be desired in terms of accuracy and explainability. Therefore, involving humans during verification could make the process much easier and more reliable. In this work, we propose an automated approach to detect claims that have been already manually-verified by professional fact-checkers. Our proposed approach uses recent powerful BERT variants as point-wise rerankers. Additionally, we study the impact of using different fields of the verified claim during training and inference phases. Experimental results show that our proposed pipeline outperforms the state-of-the-art approaches on two English and one Arabic datasets.
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
Publisherspringer link
SubjectClaim Retrieval
Fact Checking
Reranking
Verification
TitleDid I See It Before? Detecting Previously-Checked Claims over Twitter
TypeConference Paper
Volume Number13185 LNCS
dc.accessType Abstract Only


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