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AuthorShaar, Shaden
AuthorNikolov, Alex
AuthorBabulkov, Nikolay
AuthorAlam, Firoj
AuthorBarrón-Cedeño, Alberto
AuthorElsayed, Tamer
AuthorHasanain, Maram
AuthorSuwaileh, Reem
AuthorHaouari, Fatima
Authorda San Martino, Giovanni
AuthorNakov, Preslav
Available date2024-03-11T06:03:07Z
Publication Date2020
Publication NameCEUR Workshop Proceedings
ResourceScopus
ISSN16130073
URIhttp://hdl.handle.net/10576/52851
URIhttps://ceur-ws.org/Vol-2696/paper_265.pdf
AbstractWe present an overview of the third edition of the CheckThat! Lab at CLEF 2020. The lab featured five tasks in Arabic and English, and here we focus on the three English tasks. Task 1 challenged the participants to predict which tweets from a stream of tweets about COVID-19 are worth fact-checking. Task 2 asked to retrieve verified claims from a set of previously fact-checked claims, which could help fact-check the claims made in an input tweet. Task 5 asked to propose which claims in a political debate or a speech should be prioritized for fact-checking. A total of 18 teams participated in the English tasks, and most submissions managed to achieve sizable improvements over the baselines using models based on BERT, LSTMs, and CNNs. In this paper, we describe the process of data collection and the task setup, including the evaluation measures used, and we give a brief overview of the participating systems. Last but not least, we release to the research community all datasets from the lab as well as the evaluation scripts, which should enable further research in the important tasks of check-worthiness estimation and detecting previously fact-checked claims.
SponsorThis research is part of the Tanbih project, developed by the Qatar Computing Research Institute, HBKU and MIT-CSAIL, which aims to limit the effect of "fake news", propaganda, and media bias. The work of Tamer Elsayed and Maram Hasanain was made possible by NPRP grant# NPRP 11S-1204-170060 from the Qatar National Research Fund (a member of Qatar Foundation). The work of Reem Suwaileh was supported by GSRA grant# GSRA5-1-0527-18082 from the Qatar National Research Fund and the work of Fatima Haouari was supported by GSRA grant# GSRA6-1-0611-19074 from the Qatar National Research Fund.
Languageen
PublisherCEUR-WS
SubjectCheck-worthiness estimation
Computational journalism
COVID-19
Detecting previously fact-checked claims
Fact-checking
Social media verification
Veracity
Verified claims retrieval
TitleOverview of CheckThat! 2020 English: Automatic Identification and Verification of Claims in Social Media
TypeConference Paper
Volume Number2696
dc.accessType Abstract Only


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