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社交媒体信息过载对新冠疫情防控行为的积极影响:一个刺激—机体—反应框架

The bright side of social media information overload for anti-COVID-19 behaviors: a stimulus-organism-response framework.

作者信息

Meng Shang, Zhong Lingling, Cao Junwei

机构信息

School of Flight, Anyang Institute of Technology, Anyang, Henan, China.

School of Business, Yangzhou University, Yangzhou, China.

出版信息

Front Public Health. 2025 Apr 14;13:1556542. doi: 10.3389/fpubh.2025.1556542. eCollection 2025.

Abstract

Social media has an important impact on social management by communicating information that influences individual behavior; however, too much social media information can cause user information overload. The coronavirus disease 2019 (COVID-19) pandemic context provides an opportunity to analyze the impact of social media information overload on individuals' prosocial behaviors in emergency events. In this study, the impact of social media information overload on people's anti-COVID-19 behaviors, that is, behaviors that limit the transmission of COVID-19, was investigated by linking norm activation theory and information overload theory. Data were collected from 242 Chinese participants, and structural equation modeling was used for data analysis. The results showed that social media information overload positively influenced the awareness of consequences and the ascription of responsibility in anti-COVID-19 behaviors and that ascription of responsibility and awareness of consequences could activate people's personal norms and eventually motivate people to engage in prosocial behaviors for epidemic prevention. These findings could extend the information overload concept to a public health emergency context and yield useful insights for world pandemic control.

摘要

社交媒体通过传播影响个人行为的信息对社会管理产生重要影响;然而,过多的社交媒体信息会导致用户信息过载。2019年冠状病毒病(COVID-19)大流行背景为分析社交媒体信息过载对突发事件中个体亲社会行为的影响提供了契机。在本研究中,通过将规范激活理论与信息过载理论相联系,调查了社交媒体信息过载对人们抗击COVID-19行为(即限制COVID-19传播的行为)的影响。从242名中国参与者中收集数据,并使用结构方程模型进行数据分析。结果表明,社交媒体信息过载对人们抗击COVID-19行为中的后果意识和责任归因产生积极影响,责任归因和后果意识能够激活人们的个人规范,并最终促使人们为防疫而参与亲社会行为。这些发现可以将信息过载概念扩展到公共卫生紧急情况背景中,并为全球疫情防控提供有益的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2168/12034730/6ae8ce1d1d18/fpubh-13-1556542-g001.jpg

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