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