The COVID-19 epidemic is a global public health crisis. It is of practical significance to objectively understand the public's responses and regional differences in order to improve policy control and scientific governance during major public health threats. In this study, a topic extraction and classification model was constructed based on the Latent Dirichlet Allocation topic model and the Random Forest algorithm. Thirteen topics were identified about public opinion in the Chinese SINA microblog from January 9 to March 10, 2020. The regional distribution characteristics were explored in terms of the amount, space, time sequence, and content in major urban agglomerations including Hubei Province, Beijing-Tianjin-Hebei urban agglomeration, Yangtze River Delta, Pearl River Delta, Chengdu-Chongqing region, and some border ports of China. The results showed that the spatio-temporal distribution of public opinion is related to the severity of the epidemic, degree of population aggregation, and level of economic development. The response of Chinese people is rational and positive, and the spatial distribution within these regions is obviously different. Among the regional hotspots, Beijing-Tianjin-Hebei region is centred on Beijing; the Yangtze River Delta is centred on Shanghai, followed by Nanjing, Hangzhou and other hotspots; the Pearl River Delta is centred on Guangzhou and Shenzhen; and Hubei Province is centred on Wuhan. The time series of topics in each region are synchronously related, but there are differences in timing sequence and periodic fluctuation in response time and intensity. The imbalance of resource allocation caused by the sharp rise of relief information in the short term is prominent, and the differences in response policies of various urban agglomerations combined with regional characteristics are not obvious. We should continue to focus on public opinion on epidemic situations in key areas and accurately respond to local regions according to its actual conditions. © 2020, Science Press. All right reserved.
