2,148
Views
36
CrossRef citations to date
0
Altmetric
Original Article

How Risk Communication via Facebook and Twitter Shapes Behavioral Intentions: The Case of Fine Dust Pollution in South Korea

Pages 663-673 | Published online: 21 Aug 2019
 

ABSTRACT

Despite the importance of social network sites (SNSs) in addressing emerging public health risks, there is still a relative lack of studies examining the effects of risk communication via SNSs on risk perceptions and preventive behaviors. Based on message expression‒ and reception‒effects paradigms, this study aims to explore how expressing and receiving risk information shape preventive behavioral intentions via risk perceptions. Given the differential nature and functionality of SNSs, the present investigation also examines whether expressing and receiving risk information via two different types of SNSs—Facebook and Twitter—have different effects on risk perceptions and behavioral intentions. Analyzing survey data from 1,152 South Korean adults in the context of fine dust hazards, this study found that expressing and receiving risk information not only affected risk perceptions but also directly or indirectly influenced preventive behavioral intentions. In addition, the effects of expressing and receiving risk information were differentiated between SNS platforms, specifically Facebook and Twitter.

Additional information

Funding

This work was supported by Incheon National University Research Grant in 2018.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 215.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.