Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/9011
Title: Overview of the CLEF-2022 CheckThat! Lab Task 1 on Identifying Relevant Claims in Tweets
Authors: Nakov P.
Barrón-Cedeño A.
Da San Martino G.
Alam F.
Míguez R.
Caselli T.
Kartal Y.S.
Keywords: Check-Worthiness Estimation
Computational Journalism
COVID-19
Fact-Checking
Social Media Verification
Veracity
Laboratories
Social networking (online)
Check-worthiness estimation
Computational journalism
Fact-checking
Multiple languages
Performance
Social media
Social medium verification
Subtask
Turkishs
Veracity
COVID-19
Issue Date: 2022
Publisher: CEUR-WS
Abstract: We present an overview of CheckThat! lab 2022 Task 1, part of the 2022 Conference and Labs of the Evaluation Forum (CLEF). Task 1 asked to predict which posts in a Twitter stream are worth fact-checking, focusing on COVID-19 and politics in six languages: Arabic, Bulgarian, Dutch, English, Spanish, and Turkish. A total of 19 teams participated and most submissions managed to achieve sizable improvements over the baselines using Transformer-based models such as BERT and GPT-3. Across the four subtasks, approaches that targetted multiple languages (be it individually or in conjunction, in general obtained the best performance. We describe the dataset and the task setup, including the evaluation settings, and we give a brief overview of the participating systems. As usual in the CheckThat! lab, we release to the research community all datasets from the lab as well as the evaluation scripts, which should enable further research on finding relevant tweets that can help different stakeholders such as fact-checkers, journalists, and policymakers. © 2022 Copyright for this paper by its authors.
Description: 2022 Conference and Labs of the Evaluation Forum, CLEF 2022 -- 5 September 2022 through 8 September 2022 -- -- 181762
URI: https://hdl.handle.net/20.500.11851/9011
ISSN: 1613-0073
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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