Earticle

초록

영어

Distrust of the population in vaccination is one of the key problems of modern healthcare. Therefore, the peculiarities of the spread of anti-vaxxer narratives are a popular subject of sociological research. The largest Russian social network, VK, has several hundred communities that actively published content on the topic of vaccination against COVID-19 during the pandemic. They reflect a sharp polarization of opinion. The self-positioning of these communities makes it possible to divide them into pro-vaxxers, anti-vaxxers and neutrals. Network analysis of these communities showed differences in the behavior of supporters and opponents of vaccination in the digital space. There were significantly more communities against vaccinations. The network of anti-vaxxer communities has a significantly higher degree of density compared to pro-vaxxer communities. The leading communities according to various network criteria are the antixer communities. The results confirm the greater activity, cohesion and propensity for consolidation of anti-vaxxers compared to pro-vaxxers. The reasons are related to the characteristics of people's behavior in risky situations (prospect theory by Daniel Kahneman and Amos Tversky). In situations of health threat, people tend to take risks. Radical anti-vaxxers are seeking to take advantage of this situation. Mass vaccinations are becoming a reflection of broader socio-political tensions.

목차

ABSTRACT
Ⅰ. Introduction
Ⅱ. Theoretical Foundations
2.1. The Influence of Network Communities on Opinion Formation
2.2. Cognitive Characteristics of Actors’ Behavior and Thinking
2.3. Exploitation of Social Fears by Protest Movements
Ⅲ. Research Methodology
3.1. Data Source
3.2. Data Collection
3.3. Methods of Data Analysis
Ⅳ. Results
4.1. Quantitative Analysis of Online Communities
4.2. Results of Positional Analysis: Leading Communities
4.3. Cluster Cohesion Analysis
Ⅴ. Discussion
5.1. Discussion of Findings
5.2. Implications for Research and Practice
5.3. Limitations
Ⅵ. Conclusion
Acknowledgments

저자

• Anna Yu. Sarkisova [ Researcher, Department of Public Aministration, Lomonosov Moscow State University, Russia ] Corresponding Author
• Daria O. Dunaeva [ Researcher, Department of Public Aministration, Lomonosov Moscow State University, Russia ]
• Evgeny Yu. Petrov [ Technical Specialist, Supercomputer Center, National Research Tomsk State University, Russia ]
• Michail G. Myagkov [ Leading Researcher, Department of Public Aministration, Lomonosov Moscow State University, Russia ]

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