TY - JOUR
T1 - Overview of CheckThat! 2020 English
T2 - 11th Conference and Labs of the Evaluation Forum, CLEF 2020
AU - Shaar, Shaden
AU - Nikolov, Alex
AU - Babulkov, Nikolay
AU - Alam, Firoj
AU - Barrón-Cedeño, Alberto
AU - Elsayed, Tamer
AU - Hasanain, Maram
AU - Suwaileh, Reem
AU - Haouari, Fatima
AU - da San Martino, Giovanni
AU - Nakov, Preslav
N1 - Publisher Copyright:
Copyright © 2020 for this paper by its authors.
PY - 2020
Y1 - 2020
N2 - We present an overview of the third edition of the CheckThat! Lab at CLEF 2020. The lab featured five tasks in Arabic and English, and here we focus on the three English tasks. Task 1 challenged the participants to predict which tweets from a stream of tweets about COVID-19 are worth fact-checking. Task 2 asked to retrieve verified claims from a set of previously fact-checked claims, which could help fact-check the claims made in an input tweet. Task 5 asked to propose which claims in a political debate or a speech should be prioritized for fact-checking. A total of 18 teams participated in the English tasks, and most submissions managed to achieve sizable improvements over the baselines using models based on BERT, LSTMs, and CNNs. In this paper, we describe the process of data collection and the task setup, including the evaluation measures used, and we give a brief overview of the participating systems. 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 detecting previously fact-checked claims.
AB - We present an overview of the third edition of the CheckThat! Lab at CLEF 2020. The lab featured five tasks in Arabic and English, and here we focus on the three English tasks. Task 1 challenged the participants to predict which tweets from a stream of tweets about COVID-19 are worth fact-checking. Task 2 asked to retrieve verified claims from a set of previously fact-checked claims, which could help fact-check the claims made in an input tweet. Task 5 asked to propose which claims in a political debate or a speech should be prioritized for fact-checking. A total of 18 teams participated in the English tasks, and most submissions managed to achieve sizable improvements over the baselines using models based on BERT, LSTMs, and CNNs. In this paper, we describe the process of data collection and the task setup, including the evaluation measures used, and we give a brief overview of the participating systems. 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 detecting previously fact-checked claims.
KW - COVID-19
KW - Check-worthiness estimation
KW - Computational journalism
KW - Detecting previously fact-checked claims
KW - Fact-checking
KW - Social media verification
KW - Veracity
KW - Verified claims retrieval
UR - http://www.scopus.com/inward/record.url?scp=85121825777&partnerID=8YFLogxK
M3 - Conference article
AN - SCOPUS:85121825777
SN - 1613-0073
VL - 2696
JO - CEUR Workshop Proceedings
JF - CEUR Workshop Proceedings
Y2 - 22 September 2020 through 25 September 2020
ER -