Research on the Dissemination Characteristics of Public Opinion on Weibo in COVID-19: Based on Emotional Analysis and Social Network

ABSTRACT

With the rapid spread of COVID-19, how to deal with the public opinion caused by COVID-19 epidemic situation and correctly guide public emotion has become an urgent problem to be solved. This paper collects more than 90 000 Weibo and more than 600000 Weibo comments from January 1 to February 29, 2020. Through web crawler technology, social network analysis, SnowNLP emotion analysis and text clustering, this paper analyzes the public opinion related topics of COVID-19, shows the evolution of public opinion in time, and finds that the change of Weibo emotion in this period is roughly divided into four stages. That is, the initial panic and anxiety about the unknown virus, the temporary relaxation after official clarification, the emotional ups and downs during the worst period of the epidemic and finally the confident and stable period of fighting the epidemic, at the same time, the emotional changes of key users will affect the overall emotional changes in the same direction during this period. © 2021 IEEE.