Public Opinion Analysis of COVID-19 Transmission in China Based on Weibo Texts (Preprint)

BACKGROUND Background: The outbreak of COVID-19 in 2019 had a huge impact on the world, and netizens also showed great concern about the pandemic situation. OBJECTIVE Objective: To analyze the public opinion trend on the COVID-19 pandemic and netizens’ sentimental attitudes to help grasp the dynamics of public sentiment toward the event and provide a reference for the government and the media to steer public opinion. METHODS Methods: Four time points were selected during the pandemic according to the Weibo Index. Weibo content were grabbed by crawlers. A total of 510,493 Weibo texts were collected. Regional analysis, word frequency statistics and sentiment analysis were conducted based on the Weibo content. RESULTS Results: The pandemic aroused great concern of Internet user. Among the four time points selected, Beijing users had the highest attention(about 9.28%). Wordcloud showed that the words “pneumonia”, “novel coronavirus pneumonia”, “coronavirus”, “case” and “Wuhan” were the main concerns of Weibo users. At the first time point, about 47% of netizens showed negative emotions and it was higher than the percentage of positive emotions (about 35%). But at the time point 2, 3, 4, the netizens with positive emotions accounted for 41%, 51% and 47% respectively, which were significantly greater than those with negative emotions (30%, 26% and 29%). CONCLUSIONS Conclusions: The pandemic caused great concern among netizens with a higher level of concern in economically developed regions. In Weibo users’ posts, words related to COVID-19 and fighting the pandemic were used most frequently during the pandemic. In the early days of the outbreak, netizens were panicked by the outbreak. Over time, the mood of netizens gradually shifted toward confidence and hope.