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ArCOV19-Rumors: Arabic COVID-19 Twitter Dataset for Misinformation Detection

2020-10-17 11:21:40
Fatima Haouari, Maram Hasanain, Reem Suwaileh, Tamer Elsayed
arXiv_CL
       
Abstract

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. We then manually-annotated the tweets by veracity to support research on misinformation detection, which is one of the major problems faced during a pandemic. We aim to support two classes of misinformation detection problems 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.

Abstract (translated)

URL

https://arxiv.org/abs/2010.08768

PDF

https://arxiv.org/pdf/2010.08768.pdf

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