Author: Richard J. Medford; Sameh N. Saleh; Andrew Sumarsono; Trish M. Perl; Christoph U. Lehmann
Title: An ""Infodemic"": Leveraging High-Volume Twitter Data to Understand Public Sentiment for the COVID-19 Outbreak Document date: 2020_4_7
ID: a6p6ka8w_33
Snippet: In this study, we demonstrate significant persistent increases in overall Twitter activity, tweets with negative sentiment and emotions, and racially charged content for the COVID-19 outbreak from January 21, 2020 onward. We show that the frequency of tweets was associated with the number of infected individuals for the early stages of the COVID-19 outbreak. Tweets predominantly showed negative sentiment and were linked to emotions of fear primar.....
Document: In this study, we demonstrate significant persistent increases in overall Twitter activity, tweets with negative sentiment and emotions, and racially charged content for the COVID-19 outbreak from January 21, 2020 onward. We show that the frequency of tweets was associated with the number of infected individuals for the early stages of the COVID-19 outbreak. Tweets predominantly showed negative sentiment and were linked to emotions of fear primarily, as well as surprise and anger. While tweets with misinformation and societal prejudice were present, tweets were also significantly used to disseminate valuable public health information. These data may help medical experts and public health officials to identify types of communication and messaging that may allay emotion and decrease misinformation.
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