Cargando…

Netizens’ risk perception in new coronary pneumonia public health events: an analysis of spatiotemporal distribution and influencing factors

BACKGROUND: Internet search volume reflects the level of Internet users’ risk perception during public health events. The Internet search volume index model, an algorithm of concentration of Internet users, and statistical analysis of popular topics on Weibo are used to analyze the effects of time,...

Descripción completa

Detalles Bibliográficos
Autores principales: Li, Yanling, Wu, Xiancong, Wang, Jihong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9336523/
https://www.ncbi.nlm.nih.gov/pubmed/35906584
http://dx.doi.org/10.1186/s12889-022-13852-z
Descripción
Sumario:BACKGROUND: Internet search volume reflects the level of Internet users’ risk perception during public health events. The Internet search volume index model, an algorithm of concentration of Internet users, and statistical analysis of popular topics on Weibo are used to analyze the effects of time, space, and space-time interaction. We conducted in-depth research on the characteristics of the spatial and temporal distribution of Internet users’ risk perceptions of public health events and the associated influential factors. METHODS: We analyzed the spatiotemporal distribution characteristics of Internet users’ risk perception after the Wuhan “city closing” order during the coronavirus disease 2019 (COVID-19) pandemic. We established five linear regression models according to different time periods and analyzed factors influencing Internet users’ risk perception by employing a Poisson and spatial distribution and topic modeling analysis. RESULTS: Economy, education, health, and the degree of information disclosure affect Internet users’ risk perception significantly. Internet users’ risk perception conforms to the exponential distribution law in time and has periodic characteristics and stability trends. Additionally, Internet users’ average arrival rate dropped from week 1 to week 8 after the “city closing.” Internet users’ risk perception has a uniform distribution in space, economic and social development level distribution consistency, spatial agglomeration, and other characteristics. The results of the time-space interaction show that after 8 weeks of COVID-19, Internet search hot topics have become more stable, and Internet users’ information demand structure has become more rational. CONCLUSIONS: The Internet search cycle of the COVID-19 event is synchronized with the evolution cycle of the epidemic. The physical risk of Internet users is at the top of the risk structure, focusing on the strong concern about the government’s ability to control COVID-19 and its future trend. The government should strengthen network management; seize the risk control focus of key time nodes, regional locations, and information content of online communication; actively adjust the information content supply; effectively control the rebound of Internet users’ risk perception; establish a data-driven, risk-aware intelligence system for internet users; and guide people to actively face and overcome the potential risks and threats of COVID-19.