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AuthorBarrón-Cedeño, Alberto
AuthorElsayed, Tamer
AuthorNakov, Preslav
AuthorDa San Martino, Giovanni
AuthorHasanain, Maram
AuthorSuwaileh, Reem
AuthorHaouari, Fatima
AuthorBabulkov, Nikolay
AuthorHamdan, Bayan
AuthorNikolov, Alex
AuthorShaar, Shaden
AuthorAli, Zien Sheikh
Available date2024-03-11T06:03:06Z
Publication Date2020
Publication NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ResourceScopus
ISSN3029743
URIhttp://dx.doi.org/10.1007/978-3-030-58219-7_17
URIhttp://hdl.handle.net/10576/52842
AbstractWe present an overview of the third edition of the CheckThat! Lab at CLEF 2020. The lab featured five tasks in two different languages: English and Arabic. The first four tasks compose the full pipeline of claim verification in social media: Task 1 on check-worthiness estimation, Task 2 on retrieving previously fact-checked claims, Task 3 on evidence retrieval, and Task 4 on claim verification. The lab is completed with Task 5 on check-worthiness estimation in political debates and speeches. A total of 67 teams registered to participate in the lab (up from 47 at CLEF 2019), and 23 of them actually submitted runs (compared to 14 at CLEF 2019). Most teams used deep neural networks based on BERT, LSTMs, or CNNs, and achieved sizable improvements over the baselines on all tasks. Here we describe the tasks setup, the evaluation results, and a summary of the approaches used by the participants, and we discuss some lessons learned. 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 automatic claim verification.
SponsorAcknowledgments. This work was made possible in part 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. 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. This research is also part of the Tanbih project, which aims to limit the effect of disinformation, "fake news", propaganda, and media bias.
Languageen
PublisherSpringer Science and Business Media Deutschland GmbH
SubjectCheck-worthiness estimation
Computational journalism
Detecting previously fact-checked claims
Evidence-based verification
Fact-checking
Social media verification
Veracity
TitleOverview of CheckThat! 2020: Automatic Identification and Verification of Claims in Social Media
TypeConference Paper
Pagination215-236
Volume Number12260 LNCS


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