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Extracting COVID-19 Events from Twitter

Published time: 04 June 2020

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


Abstract

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 https://github.com/viczong/extract_COVID19_events_from_Twitter


Extracting COVID-19 Events from Twitter

 

Reference: https://arxiv.org/abs/2006.02567v1

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