Extracting COVID-19 Events from Twitter
Year: 2020
Type: preprint
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 this https URL
Source: arXiv (Cornell University)
Authors: Shi Zong, Ashutosh Baheti, Wei Xu, Alan Ritter
Language: English
Topic: Topic Modeling
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W3033999739