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How Does Risk-Information Communication Affect the Rebound of Online Public Opinion of Public Emergencies in China?

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  • Shan Gao

    (School of Public Administration, Central South University, Changsha 410083, China
    School of Economic Management and Law, University of South China, Hengyang 421001, China)

  • Ye Zhang

    (School of Public Administration, Central South University, Changsha 410083, China)

  • Wenhui Liu

    (School of Public Administration, Central South University, Changsha 410083, China)

Abstract

The rebound of online public opinion is an important driving force in inducing a secondary crisis in the case of public emergencies. Effective risk-information communication is an important means to manage online public opinion regarding emergencies. This paper employs fuzzy-set qualitative comparative analysis to discover which conditions are combined and may result in the rebound of online public opinion. Five conditions were selected: the type of public emergency, messengers, message attributes, audience, and information feedback. The study used a sample of 25 major public emergencies that occurred between 2015 and 2020 in China. The type of public emergency, audience, and information feedback emerged as critical influencing factors. Message attributes promote the rebound of online public opinion regarding public health emergencies, while messengers play a traction role in the rebound of online public opinion on other types of public emergencies. This study extends risk-information communication theory from the perspective of the type of emergency, explores the causes of rebounded online public opinion regarding public emergencies, and provides policies and suggestions for risk-information communication and online public-opinion governance during emergencies.

Suggested Citation

  • Shan Gao & Ye Zhang & Wenhui Liu, 2021. "How Does Risk-Information Communication Affect the Rebound of Online Public Opinion of Public Emergencies in China?," IJERPH, MDPI, vol. 18(15), pages 1-14, July.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:15:p:7760-:d:599006
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    Cited by:

    1. Yu Lei & Guirong Zhang & Shan Lu & Jiahuan Qian, 2022. "Generation Paths of Major Road Accidents Based on Fuzzy-Set Qualitative Comparative Analysis," IJERPH, MDPI, vol. 19(21), pages 1-15, October.
    2. Chao Zhang & Ning Ma & Guohui Sun, 2022. "Using Grounded Theory to Identify Online Public Opinion in China to Improve Risk Management—The Case of COVID-19," IJERPH, MDPI, vol. 19(22), pages 1-17, November.

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