Abstract
The study aims to understand Twitter users’ discourse and psychological reactions to COVID-19. We use machine learning techniques to analyze about 1.9 million Tweets (written in English) related to coronavirus collected from January 23 to March 7, 2020. A total of salient 11 topics are identified and then categorized into ten themes, including “updates about confirmed cases,” “COVID-19 related death,” “cases outside China (worldwide),” “COVID-19 outbreak in South Korea,” “early signs of the outbreak in New York,” “Diamond Princess cruise,” “economic impact,” “Preventive measures,” “authorities,” and “supply chain.” Results do not reveal treatments and symptoms related messages as prevalent topics on Twitter. Sentiment analysis shows that fear for the unknown nature of the coronavirus is dominant in all topics. Implications and limitations of the study are also discussed.
Highlights
WHO declares COVID-19 as a global health pandemic
Aiming to explore the public discourse and psychological reactions during the early stage of COVID-19, we use a machine learning approach to examine (1) What latent topics related to COVID-19 can we identify from these Tweets? (2) What are the themes of these identified topics? (3) How Twitter users emotionally react to COVID-19 pandemic? And (4) How do these sentiments change over time?
This study shows Twitter users’ discussions and sentiments to the COVID-19 from January 23 to March 7, 2020
Summary
WHO declares COVID-19 as a global health pandemic. Social media has played a crucial role before the virus outbreak and continues to do so as it spreads globally. Existing studies [2,3,4,5] show that Twitter data can provide useful information for epidemic disease (e.g., H1N1, Ebola), including tracking rapidly evolving public sentiments, measuring public interests and concerns, estimating real-time disease activity and trends, and tracking reported disease levels. These studies have limitations, with only qualitatively manual coding a very small number of Tweets.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
