Abstract
Due to the development of the Internet and social networks, civil participation in political processes is taking new forms, not accounted for in the classical theoretical frameworks. In this study, we present a new methodology for researching these new, unconventional forms of civil participation. We use data collected from a social network site VK.com. Social network analysis methods, such as multilevel exponential random graph models (ERGM) were used to analyze the data. First proposed by Wang in 2013, multilevel ERGM allows us to model tie formation in a wide class of social networks. This method allows us to efficiently model group membership based on node attributes. Since the collected data is fundamentally 2-mode, this model allows us to identify the important factors that lead people to join online protest communities.
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Notes
- 1.
It should be noted that the VK API search function and the website search function return different results for identical requests. For this study, we have used Selenium to extract search results directly from the website.
- 2.
Public pages were included.
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Acknowledgment
The article was prepared within the framework of the Basic Research Program at the National Research University Higher School of Economics (HSE) and supported within the framework of a subsidy by the Russian Academic Excellence Project ‘5–100’.
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A Appendix: Goodness-of-fit diagnostics for the bipartite ERG model
A Appendix: Goodness-of-fit diagnostics for the bipartite ERG model
ERGM goodness-of-fit (model coefficients)
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Kuskova, V., Khvatsky, G., Zaytsev, D., Talovsky, N. (2019). Multilevel Exponential Random Graph Models Application to Civil Participation Studies. In: van der Aalst, W., et al. Analysis of Images, Social Networks and Texts. AIST 2019. Lecture Notes in Computer Science(), vol 11832. Springer, Cham. https://doi.org/10.1007/978-3-030-37334-4_24
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