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Overview of the CLEF-2023 CheckThat! Lab Task 4 on Factuality of Reporting of News Media
CEUR Workshop Proceedings
  • Preslav Nakov, Mohamed Bin Zayed University of Artificial Intelligence
  • Firoj Alam, Qatar Computing Research Institute
  • Giovanni Da San Martino, UniversitĂ  degli Studi di Padova
  • Maram Hasanain, Mohamed Bin Zayed University of Artificial Intelligence
  • Dilshod Azizov, Mohamed Bin Zayed University of Artificial Intelligence
  • Rabindra Nath Nandi, Hishab Singapore Pte. Ltd
  • Panayotov Panayot, Sofia University St. Kliment Ohridski
Document Type
Conference Proceeding
Abstract

We present an overview of the CLEF-2023 CheckThat! lab Task 4, which focused on predicting the factuality of reporting of entire news outlets. This is a different level of granularity compared to previous efforts, which focused on fact-checking, where the target is a claim, or fake news detection, where the target is an article. We briefly summarize the participating systems and discuss the dataset, the task, and the evaluation setup. The task attracted a large number of registrations, and eventually five teams made submissions. All participants improved over the baseline by a margin using both deep learning and traditional machine learning approaches. We make the dataset and the associate code freely available to the research community with the aim to promote further research on this problem.

Publication Date
9-21-2023
Keywords
  • factuality,
  • news media,
  • veracity
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Archived thanks to CEUR-WS.org

License: CC by 4.0

Uploaded: April 03, 2024

Citation Information
Preslav Nakov, Firoj Alam, Giovanni Da San Martino, Maram Hasanain, et al.. "Overview of the CLEF-2023 CheckThat! Lab Task 4 on Factuality of Reporting of News Media" CEUR Workshop Proceedings Vol. 3497 (2023) p. 260 - 268 ISSN: 16130073
Available at: http://works.bepress.com/preslav-nakov/32/