Dynamic topic modeling of the COVID-19 Twitter narrative among U.S. governors and cabinet executives
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Date
2020-04-19
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American English
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Abstract
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.
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Sha, H., Hasan, M., Mohler, G., & Brantingham, P. (2020). Dynamic topic modeling of the COVID-19 Twitter narrative among U.S. governors and cabinet executives.
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ArXiv
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Preprint