Why Do Citizens Share COVID-19 Fact-Checks Posted by Chinese Government Social Media Accounts? The Elaboration Likelihood Model

Qiang Chen, Yangyi Zhang, Richard Evans and Chen Min
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Qiang Chen: School of Journalism and New Media, Xi’an Jiaotong University, Xi’an 710049, China
Yangyi Zhang: School of Journalism and New Media, Xi’an Jiaotong University, Xi’an 710049, China
Richard Evans: Faculty of Computer Science, Dalhousie University, Halifax, NS B3H 4R2, Canada
Chen Min: College of Public Administration, Huazhong University of Science and Technology, Wuhan 430074, China

IJERPH, 2021, vol. 18, issue 19, 1-17

Abstract: Widespread misinformation about COVID-19 poses a significant threat to citizens long-term health and the combating of the disease. To fight the spread of misinformation, Chinese governments have used official social media accounts to participate in fact-checking activities. This study aims to investigate why citizens share fact-checks about COVID-19 and how to promote this activity. Based on the elaboration likelihood model, we explore the effects of peripheral cues (social media capital, social media strategy, media richness, and source credibility) and central cues (content theme and content importance) on the number of shares of fact-checks posted by official Chinese Government social media accounts. In total, 820 COVID-19 fact-checks from 413 Chinese Government Sina Weibo accounts were obtained and evaluated. Results show that both peripheral and central cues play important roles in the sharing of fact-checks. For peripheral cues, social media capital and media richness significantly promote the number of shares. Compared with the push strategy, both the pull strategy and networking strategy facilitate greater fact-check sharing. Fact-checks posted by Central Government social media accounts receive more shares than local government accounts. For central cues, content importance positively predicts the number of shares. In comparison to fact-checks about the latest COVID-19 news, government actions received fewer shares, while social conditions received more shares.

Keywords: COVID-19 misinformation; government social media; fact-checking; elaboration likelihood model; information diffusion (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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