  In this paper, we present ArCOV-19, an Arabic COVID-19 Twitter dataset that
spans one year, covering the period from 27th of January 2020 till 31st of
January 2021. ArCOV-19 is the first publicly-available Arabic Twitter dataset
covering COVID-19 pandemic that includes about 2.7M tweets alongside the
propagation networks of the most-popular subset of them (i.e., most-retweeted
and -liked). The propagation networks include both retweets and conversational
threads (i.e., threads of replies). ArCOV-19 is designed to enable research
under several domains including natural language processing, information
retrieval, and social computing. Preliminary analysis shows that ArCOV-19
captures rising discussions associated with the first reported cases of the
disease as they appeared in the Arab world. In addition to the source tweets
and propagation networks, we also release the search queries and
language-independent crawler used to collect the tweets to encourage the
curation of similar datasets.
