TY - JOUR
T1 - User Engagement in Public Discourse on Genetically Modified Organisms
T2 - The Role of Opinion Leaders on Social Media
AU - Xu, Qian
AU - Yu, Nan
AU - SONG, Celine
N1 - Funding Information:
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This project was supported by the Faculty Research and Development Reassigned-Time Fellowship at Elon University.
Funding Information:
Nan Yu, PhD, is an associate professor at University of Central Florida. Her research focuses on health communication, communication technology, and strategic communication with an emphasis on health promotion using digital technologies and health messages tailored to specific audience members. Her research has been published in premier peer-reviewed journals and was funded by National Science Foundation.
PY - 2018/12/1
Y1 - 2018/12/1
N2 - This study adopted a quantitative content analysis to examine how source attributes of opinion leaders and their message framing influenced user engagement in the public discourse of genetically modified organism (GMO) on Chinese social media. The findings showed that different source attributes and message frames used by opinion leaders varied in their respective influences on three dimensions of user engagement—reposts, comments, and likes. The attribute of account verification only predicted surface-level engagement (i.e., liking), whereas account type significantly influenced in-depth engagement (i.e., reposting and commenting). The fact, opportunity, pro-GMO, and international frames positively predicted user engagement.
AB - This study adopted a quantitative content analysis to examine how source attributes of opinion leaders and their message framing influenced user engagement in the public discourse of genetically modified organism (GMO) on Chinese social media. The findings showed that different source attributes and message frames used by opinion leaders varied in their respective influences on three dimensions of user engagement—reposts, comments, and likes. The attribute of account verification only predicted surface-level engagement (i.e., liking), whereas account type significantly influenced in-depth engagement (i.e., reposting and commenting). The fact, opportunity, pro-GMO, and international frames positively predicted user engagement.
KW - genetically modified organism
KW - opinion leader
KW - social media
KW - user engagement
KW - Weibo
UR - http://www.scopus.com/inward/record.url?scp=85056705610&partnerID=8YFLogxK
U2 - 10.1177/1075547018806526
DO - 10.1177/1075547018806526
M3 - Journal article
AN - SCOPUS:85056705610
SN - 1075-5470
VL - 40
SP - 691
EP - 717
JO - Science Communication
JF - Science Communication
IS - 6
ER -