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In recent months, COVID-19 has become a global pandemic and had a huge impacton the world. People under different conditions have very different attitudestoward the epidemic. Due to the real-time and large-scale nature of socialmedia, we can continuously obtain a massive amount of public opinioninformation related to the epidemic from social media. In particular,researchers may ask questions such as "how is the public reacting to COVID-19in China during different stages of the pandemic?", "what factors affect thepublic opinion orientation in China?", and so on. To answer such questions, weanalyze the pandemic related public opinion information on Weibo, China'slargest social media platform. Specifically, we have first collected a largeamount of COVID-19-related public opinion microblogs. We then use a sentimentclassifier to recognize and analyze different groups of users' opinions. In thecollected sentiment orientated microblogs, we try to track the public opinionthrough different stages of the COVID-19 pandemic. Furthermore, we analyze morekey factors that might have an impact on the public opinion of COVID-19 (e.g.,users in different provinces or users with different education levels).Empirical results show that the public opinions vary along with the key factorsof COVID-19. Furthermore, we analyze the public attitudes on differentpublic-concerning topics, such as staying at home and quarantine.

Tracking Public Opinion in China through Various Stages of the COVID-19 Pandemic