Sharing is caring? How moral foundation frames drive the sharing of corrective messages and misinformation about COVID-19 vaccines

Aimei Yang (), Alvin Zhou (), Jieun Shin (), Ke Huang-Isherwood (), Wenlin Liu (), Chuqing Dong (), Eugene Lee () and Jingyi Sun ()
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Aimei Yang: University of Southern California
Alvin Zhou: Hubbard School of Journalism & Mass Communication, University of Minnesota
Jieun Shin: University of Florida
Ke Huang-Isherwood: University of Southern California
Wenlin Liu: University of Florida
Chuqing Dong: Michigan State University
Eugene Lee: University of Southern California
Jingyi Sun: Stevens Institute of Technology

Journal of Computational Social Science, 2024, vol. 7, issue 3, No 17, 2733 pages

Abstract: Abstract Drawing from Moral Foundation Theory, our study explores if and how corrective messages and misinformation related to COVID-19 vaccines utilize moral frames. Unlike studies that either focused on content-analyzing messages or study how audiences react to moral frames, this study incorporated both a content analysis of COVID vaccine messages and modeling of how millions of audiences reacted to such messages. We combined semantic network analysis, text-mining, and machine learning to analyze a large corpus of Facebook posts about COVID-19 vaccines. Our results showed that both corrective messages and misinformation prevalently deployed moral framing. We also found that while corrective messages tend to highlight the virtuous aspect of morality, misinformation focuses on the sinful aspect. In both contexts, the five moral frames could construct logically self-consistent worldviews. Moreover, for corrective messages, fairness, sanctity, care, authority, and loyalty frames all significantly influence users’ message sharing. For misinformation, only the authority/subversion frame was influential.

Keywords: Moral Foundation Theory; Misinformation; Semantic network analysis; Machine learning (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s42001-024-00320-4

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