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المؤلفHaouari, Fatima
المؤلفHasanain, Maram
المؤلفSuwaileh, Reem
المؤلفElsayed, Tamer
تاريخ الإتاحة2024-11-05T06:05:19Z
تاريخ النشر2021
اسم المنشورWANLP 2021 - 6th Arabic Natural Language Processing Workshop, Proceedings of the Workshop
المصدرScopus
المعرّفhttp://dx.doi.org/10.48550/arXiv.2004.05861
معرّف المصادر الموحدhttp://hdl.handle.net/10576/60880
الملخصIn 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 languageindependent crawler used to collect the tweets to encourage the curation of similar datasets.
راعي المشروعThe 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
اللغةen
الناشرAssociation for Computational Linguistics (ACL)
الموضوعCOVID-19
Natural language processing systems
Curation
Language processing
Natural languages
Preliminary analysis
Search queries
Social computing
Social networking (online)
العنوانArCOV-19: The First Arabic COVID-19 Twitter Dataset with Propagation Networks
النوعConference Paper
الصفحات82-91
dc.accessType Open Access


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