ABSTRACT
Background
This study examined how different health organizations (i.e., the Chinese CDC, the Korean CDC, the United States CDC, and WHO) communicated about the COVID-19 pandemic on social media, thus providing implications for organizations touse social media effectively in global health crises in the future.
Methods
Three bilingual researchers conducted a content analysis ofsocial media posts (N = 1,343) of these health organizations on Twitter and Sina Weibo to explore the frames of the COVID-19 pandemic, the purposes, and the strategies to communicate about it.
Results
Prevention was the dominant frame of the social media content of these four health organizations. Information update was the major communication purpose for WHO, the United States CDC, and the Korean CDC; however, guidance was the primary communication purpose for the Chinese CDC. The United States CDC, the Chinese CDC, and the Korean CDC heavily relied on multiple social media strategies (i.e., visual, hyperlink, and authority quotation) in their communication to the public about the COVID-19 pandemic, whereas WHO primarily employed quoting authorities. Significantdifferences were revealed across these health organizations in frames, communication purposes, and strategies. Theoretical and practical implications and limitations were discussed.
Conclusions
This study examined how different global health organizations communicate about the COVID-19 pandemic on social media. We discussed how and why these global health organizations communicate the COVID-19 pandemic, which would help health-related organizations design messages strategically on global public health issues in the future.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Notes
1 As of July 2021, The COVID-19 pandemic has caused more than 35.6 million cases and 615 thousand deaths in the United States, 93 thousand cases and 4 thousand deaths in China, 207 thousand cases and 2 thousand deaths in Korea (‘COVID-19 Pandemic by Country and Territory,’ 2021).
2 RQ1b, RQ2b, and RQ3c concern the assumption of the Chi-square test [Citation41]. To meet the assumption— i.e., mutually excluded the levels (or categories) of variables [Citation24], if a single tweet falls into multiple coding categories, the post was dealt as a category named ‘mixed’ and was analyzed.
Additional information
Funding
Notes on contributors
Lingyan Ma
Lingyan Ma (Ph.D., University of Maryland) is an incoming assistant professor at Minzu University of China. Her research interest is about publics in public relations and strategic communication. Particularly, Lingyan is interested in understanding the dynamics of publics and their responses to issues and messages. ORCID: https://orcid.org/0000-0001-8889-4165
Yuan Wang
Yuan Wang (M.Phil., Chinese University of Hong Kong) is a doctoral candidate in the Department of Communication at the University of Maryland. Yuan is particularly interested in designing interventions to mitigate the negative impact of misinformation and exploring how publics seek, process, and share information about contentious issues in the emerging media environment. ORCID: https://orcid.org/0000-0002-8378-8002
Jiyoun Kim
Jiyoun Kim (Ph.D., University of Wisconsin–Madison) is an assistant professor in the Department of Communication at the University of Maryland. Jiyoun’s research is broadly concerned with science, health, and risk communication. She is particularly interested in how we can harness the power of communication to design and deliver effective messaging to help the public make more informed decisions. ORCID: https://orcid.org/0000-0002-9946-6972