新冠肺炎疫情和公众焦虑情绪的时空分异研究——基于微博数据的分析

采集河南省17个地市在COVID-19疫情期间的微博数据，利用微博数据分析疫情期间公众焦虑情绪及其时空分异。研究结果发现：公众的焦虑情绪波动幅度与疫情态势基本成正相关，疫情初期，公众对疫情数据的变化敏感，新增确诊人数的小幅增加和下降均能引起公众焦虑情绪的大幅攀升和下跌，疫情态势稳定向好时，焦虑情绪波动幅度逐渐趋稳；在疫情初期和末期，焦虑情绪与新增确诊人数呈显著正相关，在疫情中间两个阶段，焦虑情绪变化滞后于疫情变化1-3天；疫情的发生发展会触发公众焦虑情绪，但焦虑情绪不会随着疫情的稳定而消失，而随着疫情的发展被放大，并转移到日常生活的焦虑上；焦虑情绪的空间分布受到区位、经济联系、人口流动、疫情应对措施等共同影响。

SPATIOTEMPORAL DISTRIBUTION OF COVID-19 AND PUBLIC ANXIETY: ANALYSIS BASED ON MICRO-BLOG DATA

Based on the micro-blog texts of 17 cities in Henan Province, this paper analyzes the topic change of public anxiety by using semantic network analysis. On the basis of calculating the anxiety sentiment, this paper explores the temporal change of public anxiety with the development of COVID-19, and uses GIS to visualize the spatial distribution of public anxiety in 17 cities. The results show that:1) There is a positive correlation between the fluctuation range of anxiety and the epidemic. At the early stage, the public is more sensitive to the change of epidemic data. A small increase or decrease in the newly diagnosed cases can cause a sharp rise or fall in public anxiety. In the late stage, the impact gradually stabilizes. 2) In the early and late stage of the COVID-19, anxiety and the number of newly diagnosed cases changed simultaneously. In the middle two stages, the change of anxiety lagged behind the diagnosed cases number by 1-3days. 3) The focus topic of public concern is different by anxiety change. The occurrence and development of the epidemic will trigger public anxiety. Nevertheless, the anxiety will not subside with the decline of the epidemic. It will be amplified and transferred to the social anxiety in daily life, and may exist in the affected individuals for a long time. 4) The spatial distribution of public anxiety is affected by the epidemic data, and further by location, economic connection, traffic connection, population flow, epidemic response measures, etc.