Toward Using Twitter for Tracking COVID-19: A Natural Language Processing Pipeline and Exploratory Data Set
Journal of Medical Internet Research2021Vol. 23(1), pp. e25314–e25314
Citations Over TimeTop 1% of 2021 papers
Ari Z Klein, Arjun Magge, Karen O’Connor, Ivan Flores, Davy Weissenbacher, Graciela Gonzalez‐Hernandez
Abstract
We have made the 13,714 tweets identified in this study, along with each tweet's time stamp and US state-level geolocation, publicly available to download. This data set presents the opportunity for future work to assess the utility of Twitter data as a complementary resource for tracking the spread of COVID-19.
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