The CLEF-2021 CheckThat! Lab on Detecting Check-Worthy Claims, Previously Fact-Checked Claims, and Fake News
Author | Nakov, Preslav |
Author | Da San Martino, Giovanni |
Author | Elsayed, Tamer |
Author | Barrón-Cedeño, Alberto |
Author | Míguez, Rubén |
Author | Shaar, Shaden |
Author | Alam, Firoj |
Author | Haouari, Fatima |
Author | Hasanain, Maram |
Author | Babulkov, Nikolay |
Author | Nikolov, Alex |
Author | Shahi, Gautam Kishore |
Author | Struß, Julia Maria |
Author | Mandl, Thomas |
Available date | 2024-11-05T06:05:20Z |
Publication Date | 2021 |
Publication Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
Resource | Scopus |
Identifier | http://dx.doi.org/10.1007/978-3-030-72240-1_75 |
ISSN | 3029743 |
Abstract | We describe the fourth edition of the CheckThat! Lab, part of the 2021 Cross-Language Evaluation Forum (CLEF). The lab evaluates technology supporting various tasks related to factuality, and it is offered in Arabic, Bulgarian, English, and Spanish. Task 1 asks to predict which tweets in a Twitter stream are worth fact-checking (focusing on COVID-19). Task 2 asks to determine whether a claim in a tweet can be verified using a set of previously fact-checked claims. Task 3 asks to predict the veracity of a target news article and its topical domain. The evaluation is carried out using mean average precision or precision at rank k for the ranking tasks, and F1 for the classification tasks. |
Sponsor | Acknowledgments. The work of Tamer Elsayed and Maram Hasanain is made possible by NPRP grant #NPRP-11S-1204-170060 from the Qatar National Research Fund (a member of Qatar Foundation). The work of Fatima Haouari is supported by GSRA grant #GSRA6-1-0611-19074 from the Qatar National Research Fund. The statements made herein are solely the responsibility of the authors. This research is also part of the Tanbih mega-project, developed at the Qatar Computing Research Institute, HBKU, which aims to limit the effect of "fake news", propaganda, and media bias. |
Language | en |
Publisher | Springer Science and Business Media Deutschland GmbH |
Subject | Check-worthiness estimation COVID-19 Disinformation Fact-checking Fake news Misinformation Verified claim retrieval |
Type | Conference |
Pagination | 639-649 |
Volume Number | 12657 LNCS |
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