2020/10/30 by Ussama Yaqub · 1 citation
Social Sciences · Computer Science · Physics and Astronomy · #Misinformation and Its Impacts #Sentiment Analysis and Opinion Mining #Opinion Dynamics and Social Influence
paper · pdf · doi:10.1145/3428090
openalex publication_date 2020/10/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/05/21
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.