Spatio-temporal evolution and regional differences of the public opinion on the prevention and control of COVID-19 epidemic in China

被引：0

作者：

Wang J. ^{[1
,5
]}

Zhang M. ^{[1
,2
]}

Han X. ^{[1
,2
]}

Wang X. ^{[1
,3
]}

Zheng L. ^{[1
,4
]}

机构：

[1] State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing

[2] College of Resources and Environment, University of Chinese Academy of Sciences, Beijing

[3] School of Civil and Architectural Engineering, Shandong University of Technology, Zibo

[4] Institute of Disaster Prevention, Sanhe

[5] Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing

来源：

| 1600年 / Science Press卷 / 75期

关键词：

COVID-19; Epidemic prevention and control; Public opinion; Regional differences;

D O I：

10.11821/dlxb202011016

中图分类号：

学科分类号：

摘要：

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.

引用

页码：2490 / 2504

页数：14

共 21 条

[1] WHO statement on cases of COVID-19 surpassing 100000
[2] WHO statement on cases of COVID-19 could be characterized as a pandemic
[3] Fighting Covid-19 China in Action
[4] Chen E, Lerman K, Ferrara E., COVID-19: The first public coronavirus twitter dataset, (2020)
[5] Banda J M, Tekumalla R, Wang G, Et al., A large-scale COVID-19 Twitter chatter dataset for open scientific research: An international collaboration, (2020)
[6] Yin F L, Lv J H, Zhang X Y, Et al., COVID-19 information propagation dynamics in the Chinese Sina-microblog, Mathematical Biosciences and Engineering, 17, 3, pp. 2676-2692, (2020)
[7] Gao Wenbin, Chen Zhiyan, Wang Yiniu, Et al., The dynamic analysis of public concern during SARS epidemic period, Chinese Mental Health Journal, 17, 9, pp. 594-596, (2003)
[8] Lwin M O, Lu J, Sheldenkar A, Et al., Global sentiments surrounding the COVID-19 pandemic on Twitter: Analysis of Twitter trends, JMIR public health and surveillance, 6, 2, (2020)
[9] Han X H, Wang J L, Zhang M, Et al., Using social media to mine and analyze public opinion related to COVID-19 in China, International Journal of Environmental Research and Public Health, 17, 8, (2020)
[10] Xing Pengfei, Li Xinxin, Research on formation mechanism of online public opinions and guiding strategy in major epidemic prevention and control: Qualitative analysis based on online public opinion texts during the outbreak of COVID-19, Journal of Intelligence, 39, 7, pp. 67-74, (2020)

← 1 2 3 →