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

Field	Value	Language
dc.contributor.author	Allen, David E.	en
dc.contributor.author	McAleer, Michael	en
dc.date.accessioned	2022-04-28T02:44:48Z
dc.date.available	2022-04-28T02:44:48Z
dc.date.issued	2022
dc.identifier.uri	https://hdl.handle.net/2123/28253
dc.description.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.	en
dc.language.iso	en	en
dc.rights	Other	en
dc.subject	COVID-19	en
dc.subject	Coronavirus	en
dc.title	Trump's COVID-19 tweets and Dr. Fauci's emails	en
dc.type	Article	en
dc.identifier.doi	10.1007/s11192-021-04243-z
dc.relation.other	Ministry of Science and Technology	en
dc.relation.other	Australian Research Council	en
usyd.faculty	Faculty of Science, School of Mathematics and Statistics

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