Mega-COV: A Billion-Scale Dataset of 100+Languages for COVID-19
16th Conference of the European Chapter of the Association for Computational Linguistics (Eacl 2021)
; : 3402-3420, 2021.
Article
in English
| Web of Science | ID: covidwho-2156484
ABSTRACT
We describe mega-COV, a billion-scale dataset from Twitter for studying COVID-19. The dataset is diverse (covers 268 countries), longitudinal (goes as back as 2007), multilingual (comes in 100+ languages), and has a significant number of location-tagged tweets (similar to 169M tweets). We release tweet IDs from the dataset. We also develop two powerful models, one for identifying whether or not a tweet is related to the pandemic (best F-1 =97%) and another for detecting misinformation about COVID-19 (best F-1 =92%). A human annotation study reveals the utility of our models on a subset of Mega-COV. Our data and models can be useful for studying a wide host of phenomena related to the pandemic. Mega-COV and our models are publicly available.
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Collection:
Databases of international organizations
Database:
Web of Science
Language:
English
Journal:
16th Conference of the European Chapter of the Association for Computational Linguistics (Eacl 2021)
Year:
2021
Document Type:
Article
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