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Cities. 2022 Jan;120:103490. doi: 10.1016/j.cities.2021.103490. Epub 2021 Oct 8.
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Environ Sci Pollut Res Int. 2021 Aug;28(32):43732-43746. doi: 10.1007/s11356-021-13653-8. Epub 2021 Apr 10.
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Using Baidu search values to monitor and predict the confirmed cases of COVID-19 in China: - evidence from Baidu index.利用百度搜索指数监测和预测中国新冠肺炎确诊病例:来自百度指数的证据。
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Transbound Emerg Dis. 2021 Nov;68(6):3643-3657. doi: 10.1111/tbed.13973. Epub 2021 Jan 29.
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The psychological burden experienced by Chinese citizens during the COVID-19 outbreak: prevalence and determinants.中国公民在 COVID-19 疫情期间的心理负担:流行率及决定因素。
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Online Public Attention During the Early Days of the COVID-19 Pandemic: Infoveillance Study Based on Baidu Index.新冠疫情早期的网络公众关注度:基于百度指数的信息监测研究。
JMIR Public Health Surveill. 2020 Oct 22;6(4):e23098. doi: 10.2196/23098.

揭示中国疫情危机期间公众恐慌水平的时空特征。

Revealing the spatiotemporal characteristics of the general public's panic levels during the pandemic crisis in China.

作者信息

Chen Yuanyi, Liu Yi, Yan Yingwei

机构信息

School of Geography and Planning Sun Yat-sen University Guangzhou China.

Department of Geography National University of Singapore Singapore.

出版信息

Trans GIS. 2022 Dec 26. doi: 10.1111/tgis.13016.

DOI:10.1111/tgis.13016
PMID:36721464
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9880711/
Abstract

The existing crisis management research mostly reveals the patterns of the public's panic levels from the perspectives of public management, sociology, and psychology, only a few studies have revealed the spatiotemporal characteristics. Therefore, this study investigates the spatial distribution and temporal patterns and influencing factors on the general public's panic levels using the Baidu Index data from a geographic perspective. The results show that: (1) The public's panic levels were significantly correlated with the spatial distance between the epicenter and the region of investigation, and with the number of confirmed cases in different regions when the pandemic began to spread. (2) Based on the spatial distance between the epicenter and the region, the public's panic levels in different regions could be divided into three segments: core segment (0-500 km), buffer segment (500-1300 km), and peripheral segment (>1300 km). The panic levels of different people in the three segments were consistent with the Psychological Typhoon Eye Effect and the Ripple Effect can be detected in the buffer segment. (3) The public's panic levels were strongly correlated with whether the spread of the infectious disease crisis occurred and how long it lasted. It is suggested that crisis information management in the future needs to pay more attention to the spatial division of control measures. The type of crisis information released to the general public should depend on the spatial relationship associated with the place where the crisis breaks out.

摘要

现有的危机管理研究大多从公共管理、社会学和心理学的角度揭示公众恐慌水平的模式,只有少数研究揭示了时空特征。因此,本研究从地理学角度利用百度指数数据,调查公众恐慌水平的空间分布、时间模式及其影响因素。结果表明:(1)公众恐慌水平与疫情爆发时震中与调查地区的空间距离以及不同地区的确诊病例数显著相关。(2)根据震中与地区的空间距离,不同地区公众的恐慌水平可分为三个区段:核心区段(0 - 500公里)、缓冲区段(500 - 1300公里)和外围区段(>1300公里)。三个区段不同人群的恐慌水平符合心理台风眼效应,在缓冲区段可检测到涟漪效应。(3)公众恐慌水平与传染病危机是否发生及其持续时间密切相关。建议未来的危机信息管理需要更加关注控制措施的空间划分。向公众发布的危机信息类型应取决于与危机爆发地相关的空间关系。