ArCorona: Analyzing Arabic Tweets in the Early Days of Coronavirus (COVID-19) Pandemic
December 02, 2020 ยท Declared Dead ยท ๐ International Workshop on Health Text Mining and Information Analysis
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Authors
Hamdy Mubarak, Sabit Hassan
arXiv ID
2012.01462
Category
cs.CL: Computation & Language
Cross-listed
cs.SI
Citations
25
Venue
International Workshop on Health Text Mining and Information Analysis
Last Checked
4 months ago
Abstract
Over the past few months, there were huge numbers of circulating tweets and discussions about Coronavirus (COVID-19) in the Arab region. It is important for policy makers and many people to identify types of shared tweets to better understand public behavior, topics of interest, requests from governments, sources of tweets, etc. It is also crucial to prevent spreading of rumors and misinformation about the virus or bad cures. To this end, we present the largest manually annotated dataset of Arabic tweets related to COVID-19. We describe annotation guidelines, analyze our dataset and build effective machine learning and transformer based models for classification.
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