Trump's COVID-19 tweets and Dr. Fauci's emails

David E Allen; Michael McAleer

doi:10.1007/s11192-021-04243-z

Trump's COVID-19 tweets and Dr. Fauci's emails

Scientometrics. 2022;127(3):1643-1655. doi: 10.1007/s11192-021-04243-z. Epub 2022 Jan 16.

Authors

David E Allen^{1

2

3}, Michael McAleer^{2

4

5

6

7}

Affiliations

¹ School of Mathematics and Statistics, University of Sydney, Sydney, Australia.
² Department of Finance, College of Management, Asia University, Taichung City, Taiwan.
³ School of Business and Law, Edith Cowan University, Joondalup, Australia.
⁴ Department of Bioinformatics and Medical Engineering, College of Information and Electrical Engineering, Asia University, Taichung City, Taiwan.
⁵ Discipline of Business Analytics, University of Sydney Business School, Sydney, Australia.
⁶ Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, The Netherlands.
⁷ Department of Economic Analysis and ICAE, Complutense University of Madrid, Madrid, Spain.

Abstract

The paper features an analysis of former President Trump's early tweets on COVID-19 in the context of Dr. Fauci's recently revealed email trove. The tweets are analysed using various data mining techniques, including sentiment analysis. These techniques facilitate exploration of content and sentiments within the texts, and their potential implications for the national and international reaction to COVID-19. The data set or corpus includes 159 tweets on COVID-19 that are sourced from the Trump Twitter Archive, running from 24 January 2020 to 2 April 2020. In addition we use Zipf and Mandelbrot's power law to calibrate the extent to which they differ from normal language patterns. A context for the emails is provided by the recently revealed email trove of Dr. Fauci, obtained by Buzzfeed on 1 June 2021 obtained under the Freedom of Information Act.

Keywords: COVID 19; Dr Fauci emails; Sentiment analysis; Stock market; Text mining; Trump; Tweets; Word cloud.