ArCOV19-Rumors: Arabic COVID-19 Twitter Dataset for Misinformation Detection
المؤلف | Haouari, Fatima |
المؤلف | Hasanain, Maram |
المؤلف | Suwaileh, Reem |
المؤلف | Elsayed, Tamer |
تاريخ الإتاحة | 2024-03-11T06:03:07Z |
تاريخ النشر | 2021 |
اسم المنشور | WANLP 2021 - 6th Arabic Natural Language Processing Workshop, Proceedings of the Workshop |
المصدر | Scopus |
الملخص | In this paper we introduce ArCOV19-Rumors, an Arabic COVID-19 Twitter dataset for misinformation detection composed of tweets containing claims from 27th January till the end of April 2020. We collected 138 verified claims, mostly from popular fact-checking websites, and identified 9.4K relevant tweets to those claims. Tweets were manually-annotated by veracity to support research on misinformation detection, which is one of the major problems faced during a pandemic. ArCOV19-Rumors supports two levels of misinformation detection over Twitter: Verifying free-text claims (called claim-level verification) and verifying claims expressed in tweets (called tweet-level verification). Our dataset covers, in addition to health, claims related to other topical categories that were influenced by COVID-19, namely, social, politics, sports, entertainment, and religious. Moreover, we present benchmarking results for tweet-level verification on the dataset. We experimented with SOTA models of versatile approaches that either exploit content, user profiles features, temporal features and propagation structure of the conversational threads for tweet verification. |
راعي المشروع | 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. |
اللغة | en |
الناشر | Association for Computational Linguistics (ACL) |
الموضوع | Natural language processing systems Social networking (online) User profile Free texts Health claims Profile features Social politics Temporal features Temporal propagation User's profiles COVID-19 |
النوع | Conference Paper |
الصفحات | 72-81 |
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