Publication | Open Access
Tweeting During the Covid-19 Pandemic
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Citations
17
References
2020
Year
Social MediaSocial Medium MiningHealth CommunicationGlobal HealthEarly SpreadCovid-19 PandemicSocial DistancingPolitical CommunicationCommunicationSocial Medium DataArtsContent AnalysisUnited StatesSentiment AnalysisText MiningCovid-19
In this article, we utilize VADER, a rule-based model, to perform sentiment analysis of tweets by President Donald Trump during the early spread of the Covid-19 pandemic across the United States, making it the worst-hit country in the world. We discover a statistically significant negative correlation between the sentiment of his messages and the number of Covid-19 cases in the United States, indicating an effect on the tone of his tweets as the pandemic took its toll on American lives and economy. Furthermore, we also witness a gradual shift from positive to negative sentiment in his messages mentioning China and coronavirus together.
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