CheckThat! at CLEF 2020: Enabling the automatic identification and verification of claims in social media
| Author | Barrón-Cedeño, Alberto |
| Author | Elsayed, Tamer |
| Author | Nakov, Preslav |
| Author | Da San Martino, Giovanni |
| Author | Hasanain, Maram |
| Author | Suwaileh, Reem |
| Author | Haouari, Fatima |
| Available date | 2024-03-11T06:03:06Z |
| Publication Date | 2020 |
| Publication Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
| Resource | Scopus |
| ISSN | 3029743 |
| Abstract | We describe the third edition of the CheckThat! Lab, which is part of the 2020 Cross-Language Evaluation Forum (CLEF). CheckThat! proposes four complementary tasks and a related task from previous lab editions, offered in English, Arabic, and Spanish. Task 1 asks to predict which tweets in a Twitter stream are worth fact-checking. Task 2 asks to determine whether a claim posted in a tweet can be verified using a set of previously fact-checked claims. Task 3 asks to retrieve text snippets from a given set of Web pages that would be useful for verifying a target tweet's claim. Task 4 asks to predict the veracity of a target tweet's claim using a set of potentially-relevant Web pages. Finally, the lab offers a fifth task that asks to predict the check-worthiness of the claims made in English political debates and speeches. CheckThat! features a full evaluation framework. The evaluation is carried out using mean average precision or precision at rank k for ranking tasks, and F1 for classification tasks. |
| Sponsor | Acknowledgments. The work of Tamer Elsayed and Maram Hasanain was made possible by NPRP grant# NPRP 11S-1204-170060 from the Qatar National Research Fund (a member of Qatar Foundation). The work of Reem Suwaileh was supported by GSRA grant# GSRA5-1-0527-18082 from the Qatar National Research Fund and the work of Fatima Haouari was 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 project, developed by the Qatar Computing Research Institute, HBKU and MIT-CSAIL, which aims to limit the effect of "fake news", propaganda, and media bias. |
| Language | en |
| Publisher | Springer |
| Subject | Automation Forecasting Websites Classification tasks Cross-language evaluation forums Evaluation framework Political debates Social media Text snippets Social networking (online) |
| Type | Conference Paper |
| Pagination | 499-507 |
| Volume Number | 12036 LNCS |
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