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Overview of the CLEF-2019 CheckThat! Lab: Automatic Identification and Verification of Claims

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Book cover Experimental IR Meets Multilinguality, Multimodality, and Interaction (CLEF 2019)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11696))

Abstract

We present an overview of the second edition of the CheckThat! Lab at CLEF 2019. The lab featured two tasks in two different languages: English and Arabic. Task 1 (English) challenged the participating systems to predict which claims in a political debate or speech should be prioritized for fact-checking. Task 2 (Arabic) asked to (A) rank a given set of Web pages with respect to a check-worthy claim based on their usefulness for fact-checking that claim, (B) classify these same Web pages according to their degree of usefulness for fact-checking the target claim, (C) identify useful passages from these pages, and (D) use the useful pages to predict the claim’s factuality. CheckThat! provided a full evaluation framework, consisting of data in English (derived from fact-checking sources) and Arabic (gathered and annotated from scratch) and evaluation based on mean average precision (MAP) and normalized discounted cumulative gain (nDCG) for ranking, and F\(_1\) for classification. A total of 47 teams registered to participate in this lab, and fourteen of them actually submitted runs (compared to nine last year). The evaluation results show that the most successful approaches to Task 1 used various neural networks and logistic regression. As for Task 2, learning-to-rank was used by the highest scoring runs for subtask A, while different classifiers were used in the other subtasks. 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.

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Notes

  1. 1.

    http://sites.google.com/view/clef2019-checkthat/datasets-tools.

  2. 2.

    http://idir.uta.edu/claimbuster/.

  3. 3.

    Their claim crawling tool: http://github.comx/vwoloszyn/fake_news_extractor.

  4. 4.

    In 2018, we had a different fact-checking task, where no retrieved Web pages were provided [6].

  5. 5.

    http://tanbih.qcri.org/.

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Acknowledgments

This work was made possible in part by NPRP grant# NPRP 7-1330-2-483 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.

This research is also part of the Tanbih project,Footnote 5 which aims to limit the effect of “fake news”, propaganda and media bias by making users aware of what they are reading. The project is developed in collaboration between the Qatar Computing Research Institute (QCRI), HBKU and the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL).

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Authors and Affiliations

  1. Computer Science and Engineering Department, Qatar University, Doha, Qatar

    Tamer Elsayed, Maram Hasanain & Reem Suwaileh

  2. Qatar Computing Research Institute, HBKU, Doha, Qatar

    Preslav Nakov & Giovanni Da San Martino

  3. DIT, Università di Bologna, Forlì, Italy

    Alberto Barrón-Cedeño

  4. Department of Computer Science, University of Copenhagen, Copenhagen, Denmark

    Pepa Atanasova

Authors
  1. Tamer Elsayed
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  2. Preslav Nakov
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  3. Alberto Barrón-Cedeño
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  4. Maram Hasanain
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  5. Reem Suwaileh
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  6. Giovanni Da San Martino
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  7. Pepa Atanasova
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Correspondence to Maram Hasanain .

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Editors and Affiliations

  1. Universita della Svizzera Italiana, Lugano, Switzerland

    Fabio Crestani

  2. Zurich University of Applied Sciences, Winterthur, Switzerland

    Martin Braschler

  3. University of Neuchâtel, Neuchâtel, Switzerland

    Jacques Savoy

  4. Technische Universität Wien, Vienna, Austria

    Andreas Rauber

  5. HES-SO Valais-Wallis, Sierre, Switzerland

    Henning Müller

  6. University of Santiago de Compostela, Santiago de Compostela, Spain

    David E. Losada

  7. Swiss Alliance for Data-Intensive Services, Thun, Switzerland

    Gundula Heinatz Bürki

  8. University of Padua, Padua, Italy

    Linda Cappellato

  9. University of Padua, Padua, Italy

    Nicola Ferro

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Elsayed, T. et al. (2019). Overview of the CLEF-2019 CheckThat! Lab: Automatic Identification and Verification of Claims. In: Crestani, F., et al. Experimental IR Meets Multilinguality, Multimodality, and Interaction. CLEF 2019. Lecture Notes in Computer Science(), vol 11696. Springer, Cham. https://doi.org/10.1007/978-3-030-28577-7_25

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  • DOI: https://doi.org/10.1007/978-3-030-28577-7_25

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