RAPID NSF Collaborative Research:
Quantifying Social Media Data for Improved Modeling of Mitigation Strategies for the COVID-19 pandemic
Mission of the project
This research aims to provide needed knowledge and methods for the development of a model of how individuals in the U.S. react to certain mitigation strategies, such as social-distancing, stay-at-home orders, quarantines, and travel advisories, by mining and analyzing social media data during the COVID-19 crisis.
1M+
Tweets related to mitigation strategies have been downloaded
215
Days since the start of the data collection
3
Mitigation Strategies (Masks wearing, Social Distancing, and Quarantine)
83,000+
Unique Twitter Users
Map of the United States depicting the sentiments for a sample of the labeled tweets (1%) posted from June 10th,2020 since December 31st,2020 for each mitigation strategies. The tweets are labeled as positive for compliance (green) or negative for resistance (red). The map shows also the locations of the tweet and the mitigation that the tweet mentions (mask wearing, social distancing, quarantine).
Disclaimer: The opinions, findings, and conclusions or recommendations expressed here are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
The collaborative project is supported by the National Science Foundation through awards #2029739 (Auburn University) and #2029733 (Columbus State University).