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.
| Original language | English |
|---|---|
| Pages (from-to) | 2701-2733 |
| Number of pages | 33 |
| Journal | Journal of Computational Social Science |
| Volume | 7 |
| Issue number | 3 |
| DOIs | |
| State | Published - Dec 2024 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Machine learning
- Misinformation
- Moral Foundation Theory
- Semantic network analysis
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