Your browser doesn't support javascript.
Trump's COVID-19 tweets and Dr. Fauci's emails.
Allen, David E; McAleer, Michael.
  • Allen DE; School of Mathematics and Statistics, University of Sydney, Sydney, Australia.
  • McAleer M; Department of Finance, College of Management, Asia University, Taichung City, Taiwan.
Scientometrics ; 127(3): 1643-1655, 2022.
Article in English | MEDLINE | ID: covidwho-1756855
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

Full text: Available Collection: International databases Database: MEDLINE Type of study: Reviews Language: English Journal: Scientometrics Year: 2022 Document Type: Article Affiliation country: S11192-021-04243-z

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Type of study: Reviews Language: English Journal: Scientometrics Year: 2022 Document Type: Article Affiliation country: S11192-021-04243-z