Russia’s Online Opposition Communities Before and During the Special Military Operation

DOI: https://doi.org/10.15826/csp.2025.9.3.346

Abstract

The authors mapped two clusters of communities that were most active in supporting the opposition discourse on VK, a Russian social network, in the spring of 2021 and the spring of 2024. This work was driven by the aspiration to reveal the ideological guidelines of opposition-minded netizens and measure the level of their political mobilization. A cross-temporal approach was instrumental in understanding how the historical and political context, including the Ukraine conflict, influenced the willingness and readiness of online communities to generate protests. The authors proposed a mobilization index based on self-organized criticality, a theory which has its origin in natural science. The 2021 cluster included 268 communities and consisted mainly of the liberal opposition, which, at that time, tried to urge its followers to take to the streets. Approximately 13% of the communities demonstrated a high level of mobilization. Over the next two years, the core of this liberal protest infrastructure ceased to exist online. Courts and prosecutors dismantled the majority of mobilized and influential communities. The 2024 cluster, which consisted of 200 communities, emerged as a reflection of the discussion about the strategic goals and tactics of the special military operation (SMO). The liberal segment still existed, though such communities demonstrated a minimal level of mobilization. Russian nationalists dominated the 2024 cluster. Many of their communities (approximately 27%) have mobilized and effectively influenced the opinions, views, and motivation of other users. The SMO has led to a change in the dominant ideas that shape the opposition discourse online. Liberal talking points have lost the initiative, and now that initiative has been seized by nationalist talking points, which are focused on winning the SMO, intensifying military operations, and “eradicating internal enemies” including pro-Western liberals and migrants.

Author Biographies

Dmitry S. Zhukov, Derzhavin Tambov State University, Tambov

Dmitry S. Zhukov, Cand. Sci. (History) from Tambov State University, Russia (2003). He is an Associate Professor at the Department of Political Science, Sociology, and International Processes of Tambov State University. He launched the development of fractal computer models with the purpose to simulate phenomena and processes in social and political spheres.

Sergey K. Lyamin, Derzhavin Tambov State University, Tambov

Sergey K. Lyamin, Cand. Sci. (History) from Tambov State University (2003). He is an Associate Professor at the Department of Russian History of Tambov State University. His main research interests concern social and historical anthropology, as well as computer simulation of social processes. Together with Dmitry Zhukov, he is a founder and a scientific supervisor of the Center for Fractal Modeling.

Dmitry G. Seltser, Derzhavin Tambov State University, Tambov

Dmitry G. Seltser, Dr. Sci. (Political Science) from Lomonosov Moscow State University (2007). His professional interests include contemporary Russian politics, regional elitology, and cross-country studies of political systems. Dmitry Seltser heads the Center for the Study of Political Transformations.

References


  • Açıkalın, Ş. N., & Artun, E. C. (2019). The concept of self-organized criticality: The case study of the Arab Uprising. In Ş. Ş. Erçetin & N. Potas (Eds.), Chaos, complexity and leadership 2017: Explorations of chaos and complexity theory (pp. 73–85). Springer. https://doi.org/10.1007/978-3-319-89875-9_7

  • Aguilera, M., Morer, I., Barandiaran, X., & Bedia, M. (2013). Quantifying political self-organization in social media: Fractal patterns in the Spanish 15M movement on Twitter. In ECAL 2013: The Twelfth European Conference on Artificial Life (pp. 395– 402). MIT Press. [Twitter® is a trademark of Twitter Inc., registered in the U.S. and other countries. По решению Роскомнадзора, социальная сеть Twitter полностью заблокирована в России как организация, занимающаяся распространением запрещенного контента] https://doi.org/10.7551/978-0-262-31709-2-ch057

  • Arnold, J., Bond, K., Chenoweth, E., & Pressman, J. (2018, May 31). These are the four largest protests since Trump was inaugurated. The Washington Post. https://www.washingtonpost.com/news/monkey-cage/wp/2018/05/31/these-are-the-four-largest-protests-since-trump-was-inaugurated

  • Bak, P. (1996). How nature works: The science of self-organized criticality. Copernicus. https://doi.org/10.1007/978-1-4757-5426-1

  • Bak, P., Tang, C., & Wiesenfeld, K. (1988). Self-organized criticality. Physical Review A, 38(1), 364–374. https://doi.org/10.1103/PhysRevA.38.364

  • Banerjee, S., Biswas, S., Chakrabarti, B. K., Challagundla, S. K., Ghosh, A., Guntaka, S. R., Koganti, H., Kondapalli, A. R., Maiti, R., Mitra, M., & Ram, D. R. S. (2023). Evolutionary dynamics of social inequality and coincidence of Gini and Kolkata indices under unrestricted competition. International Journal of Modern Physics C, 34(4), Article 2350048. https://doi.org/10.1142/S0129183123500481

  • Banerjee, S., Biswas, S., Chakrabarti, B. K., Ghosh, A., & Mitra, M. (2023). Sandpile universality in social inequality: Gini and Kolkata measures. Entropy, 25(5), Article 735. https://doi.org/10.3390/e25050735

  • Borodkin, L. I. (2019). Vyzovy nestabil’nosti: Kontseptsii sinergetiki v izuchenii istoricheskogo razvitiia Rossii [Challenges of instability: The concepts of synergetics in studying the historical development of Russia]. Ural Historical Journal, 2, 127–136. http://www.doi.org/10.30759/1728-9718-2019-2(63)-127-136

  • Brichoux, D., & Johnson, P. E. (2002). The power of commitment in cooperative social action. Journal of Artificial Societies and Social Simulation, 5(3).

  • Brunk, G. G. (2001). Self-organized criticality: A new theory of political behaviour and some of its implications. British Journal of Political Science, 31(2), 427–445. https://doi.org/10.1017/S0007123401000163

  • Dmitriev, A., & Dmitriev, V. (2021). Identification of self-organized critical state on Twitter based on the retweets’ time series analysis. Complexity, 2021, Article 6612785. https://doi.org/10.1155/2021/6612785

  • Dmitriev, A., Lebedev, A., Kornilov, V., & Dmitriev, V. (2023). Twitter selforganization to the edge of a phase transition: Discrete-time model and effective early warning signals in phase space. Complexity, 2023, Article 3315750. [Twitter® is a trademark of Twitter Inc., registered in the U.S. and other countries. По решению Роскомнадзора, социальная сеть Twitter полностью заблокирована в России как организация, занимающаяся распространением запрещенного контента] https://doi.org/10.1155/2023/3315750

  • Dumas, C. L., LaManna, D., Harrison, T. M., Ravi, S., Kotfila, C., Gervais, N., Hagen, L., & Chen, F. (2015). Examining political mobilization of online communities through e-petitioning behavior in We the People. Big Data & Society, 2(2). https://doi.org/10.1177/2053951715598170

  • Epstein, J. M. (2002). Modeling civil violence: An agent-based computational approach. Proceedings of the National Academy of Sciences, 99(Suppl. 3), 7243– 7250. https://doi.org/10.1073/pnas.092080199

  • Golovashina, O. V. (2017). Samoorganizovannaia kritichnost’ aktorno-setevoi teorii [Self-organized criticality of the actor-network theory]. Philosophy and Culture, 7, 23–31. https://doi.org/10.7256/2454-0757.2017.7.21658

  • Jacomy, M., Venturini, T., Heymann, S., & Bastian, M. (2014). ForceAtlas2, a continuous graph layout algorithm for handy network visualization designed for the Gephi software. PLOS ONE, 9(6), Article e98679. https://doi.org/10.1371/journal.pone.0098679

  • Kapitsa, S. P., Kurdyumov, S. P., & Malinetskii, G. G. (2001). Sinergetika i prognozy budushchego [Synergetics and forecasts of the future]. URSS.

  • Kron, T., & Grund, T. (2009). Society as a self-organized critical system. Cybernetics & Human Knowing, 16(1–2), 65–82.

  • Latonov, V. V., & Latonova, A. V. (2022). Primenenie teorii samoorganizovannoi kritichnosti k analizu liberal’noi povestki v presse 1815–1825 gg [Application of the theory of self-organized criticality to the analysis of the liberal agenda in the press of 1815–1825]. Historical Informatics, 3, 156–165. https://doi.org/10.7256/2585-7797.2022.3.38752

  • Le Goff, C. (2020, February 27). Yellow vests, rising violence—what’s happening in France? World Economic Forum. https://www.weforum.org/stories/2020/02/france-protests-yellow-vests-today

  • Lu, P., Yang, H., Li, M., & Zhang, Z. (2021). The sandpile model and empire dynamics. Chaos, Solitons & Fractals, 143, Article 110615. http://www.doi.org/10.1016/j.chaos.2020.110615

  • Makowsky, M. D., & Rubin, J. (2013). An agent-based model of centralized institutions, social network technology, and revolution. PLOS ONE, 8(11), Article e80380. https://doi.org/10.1371/journal.pone.0080380

  • Malinetskii, G. G. (2013). Chudo samoorganizovannoi kritichnosti [The miracle of self-organized criticality] [Foreword]. In P. Bak, Kak rabotaet priroda: Teoriia samoorganizovannoi kritichnosti [How nature works: The science of self-organized criticality] (V. E. Podobed, A. V. Kondrat’ev, & O. L. Shevchuk, Trans.) (pp. 13–46). URSS.

  • Maulana, A., & Situngkir, H. (2010). Power laws in elections—A survey. SSRN. https://doi.org/10.2139/ssrn.1660603

  • Picoli, S., del Castillo-Mussot, M., Ribeiro, H. V., Lenzi, E. K., & Mendes, R. S. (2014). Universal bursty behaviour in human violent conflicts. Scientific Reports, 4, Article 4773. https://doi.org/10.1038/srep04773

  • Podlazov, A. V. (2001). Novye matematicheskie modeli, metody i kharakteristiki v teorii samoorganizovannoi kritichnostii [New mathematical models, methods and characteristics in the theory of self-organized criticality] (Unpublished doctoral dissertation). Keldysh Institute of Applied Mathematics of Russian Academy of Sciences.

  • Roberts, D. C., & Turcotte, D. L. (1998). Fractality and self-organized criticality of wars. Fractals, 6(4), 351–357. https://doi.org/10.1142/S0218348X98000407

  • Schulte, F., & Trinn, C. (2024). Collective emotions, triggering events, and self-organization: The forest-fire model of cultural identity conflict escalation. Aggression and Violent Behavior, 78, Article 101954. https://doi.org/10.1016/j.avb.2024.101954

  • Shimada, I., & Koyama, T. (2015). A theory for complex system’s social change: An application of a general “criticality” model. Interdisciplinary Description of Complex Systems, 13(3), 342–353. https://doi.org/10.7906/indecs.13.3.1

  • Tadić, B., Dankulov, M. M., & Melnik, R. (2017). Mechanisms of self-organized criticality in social processes of knowledge creation. Physical Review E, 96(3), Article 32307. https://doi.org/10.1103/PhysRevE.96.032307

  • Tadić, B., Dankulov, M. M., & Melnik, R. (2023). Evolving cycles and selforganised criticality in social dynamics. Chaos, Solitons & Fractals, 171, Article 113459. https://doi.org/10.1016/j.chaos.2023.113459

  • Tadić, B., & Melnik, R. (2021). Self-organised critical dynamics as a key to fundamental features of complexity in physical, biological, and social networks. Dynamics, 1(2), 181–197. https://doi.org/10.3390/dynamics1020011

  • Thietart, R.-A. (2016). Strategy dynamics: Agency, path dependency, and self-organized emergence. Strategic Management Journal, 37(4), 774–792. https://doi.org/10.1002/smj.2368

  • Trinn, C. (2018). Criticality, entropy and conflict. Systems Research and Behavioral Science, 35(6), 746–758. https://doi.org/10.1002/sres.2516

  • Trinn, C., & Naumann, L. (2023). Guns and lightning: Power law distributions in intrastate conflict intensity dynamics. Conflict Management and Peace Science, 40(4), 373–397. https://doi.org/10.1177/07388942221092126

  • Troianovski, A., & Nechepurenko, I. (2021, August 25). Navalny10 arrested on return to Moscow in battle of wills with Putin. The New York Times. https://www.nytimes.com/2021/01/17/world/europe/navalny-russia-return.html

  • Zhukov, D. (2022). How the theory of self-organized criticality explains punctuated equilibrium in social systems. Methodological Innovations, 15(2), 163–177. https://doi.org/10.1177/20597991221100427

  • Zhukov, D. S., & Lyamin, S. K. (2017). Revoliutsii v Seti: Prilozhenie teorii samoorganizovannoi kritichnosti k izucheniiu protestnykh dvizhenii [Revolution in the Internet: Self-organized criticality theory to study protest movements]. Historical Informatics, 4, 11–43. https://doi.org/10.7256/2585-7797.2017.4.24559

Published
2025-10-10
How to Cite
Zhukov, D., Lyamin, S., & Seltser, D. (2025). Russia’s Online Opposition Communities Before and During the Special Military Operation. Changing Societies & Personalities, 9(3), 635-656. doi:10.15826/csp.2025.9.3.346
Citation Formats
Issue
Vol. 9, No. 3 (2025)
Section
Articles