Social media as amplification station: factors that influence the speed of online public response to health emergencies

ABSTRACT

Online public response to health emergencies is a major and complex public health issue. This study employs hierarchical linear modeling to investigate the speed of online users’ response to health emergency information on Chinese microblogging sites. The distribution of response speed for all posts is highly skewed. Only a minimal number of posts are forwarded in less than one minute. We further examine the effects of the characteristics of original messages as well as the effects of the factors of reposted messages and information transmitters, to determine the response time of messages on health emergencies. Original messages with different emotional orientations have different response times. The homophily of geographical location among dyadic information transmitters, the addressivity of reposted messages, and the degree of activity and popularity of information transmitters shorten the response time. This study expands the social amplification of risk model to an online context and contributes to the literature on information diffusion by identifying the effects of dyadic relationships among information transmitters. Practical implications are briefly discussed.

KEYWORDS:

• Response time
• diffusion speed
• social amplification of risk model
• natural language processing

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes on contributors

Lun Zhang is an associate professor at School of Arts & Communication, Beijing Normal University. Her research interests pertain to human communication behaviors on social media.

Linjia Xu is an assistant professor at University of International Business and Economics. She concentrates on health communication, science communication, and new media research.

Wenhao Zhang is a data scientist at Doodod Technology Co. Ltd. His research interests include natural language processing, sentiment analysis, and social media analysis.

Additional information

Funding

This work was supported by the Fundamental Research Funds for the Central Universities in China of China [grant number 310422120] and Young Scholar Program of National Social Science Funds for Young Scholar Foundation of China [grant number 14CXW015].