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Extracting COVID-19 Events from Twitter

Published time: 04 June 2020

Authors: Shi Zong, Ashutosh Baheti, Wei Xu, Alan Ritter


We present a corpus of 7,500 tweets annotated with COVID-19 events, including positive test results, denied access to testing, and more. We show that our corpus enables automatic identification of COVID-19 events mentioned in Twitter with text spans that fill a set of pre-defined slots for each event. We also present analyses on the self-reporting cases and user’s demographic information. We will make our annotated corpus and extraction tools available for the research community to use upon publication at

Extracting COVID-19 Events from Twitter



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