DOI: 10.36190/2020.21

Published: 2020-06-05
Dynamic topic modeling of the COVID-19 Twitter narrative among U.S. governors and cabinet executives
Hao Sha, Mohammad Al Hasan, George Mohler, P. Jeffrey Brantingham

A combination of federal and state-level decision making has shaped the response to COVID-19 in the United States. In this paper we analyze the Twitter narratives around this decision making by applying a dynamic topic model to COVID-19 related tweets by U.S. Governors and Presidential cabinet members. We use a network Hawkes binomial topic model to track evolving sub-topics around risk, testing and treatment. We also construct influence networks amongst government officials using Granger causality inferred from the network Hawkes process.