- information warfare; algorithmic warfare; social networks; information bubbles; information security; information resilience; hybrid aggression; strategic communications
- https://doi.org/10.33099/2617-6858-2025-87-5-7-15
- Pages 7-15
The article is devoted to the analysis of algorithmic warfare using information bubbles as a tool of Russian aggression against Ukraine. It was determined that social networks, which in peacetime perform the function of personalizing information flows, in wartime are transformed into a powerful mechanism of manipulative influence. Algorithmic systems contribute to the creation of information bubbles that isolate users from alternative perspectives, form distorted representations of events, and fuel emotionally colored narratives. The article traces the military dimension of the use of information bubbles in the structure of algorithmic warfare, shows their role in spreading panic, forming an atmosphere of mistrust and creating parallel information realities at the international level. Special attention is paid to the psychological and social consequences of the functioning of information bubbles in wartime, including the growing polarization of society, information exhaustion, the undermining of strategic communications and the narrowing of the worldview of young people. It is substantiated that countering algorithmic warfare using information bubbles requires a comprehensive approach that covers the technological, educational, state and international levels
References
- Avramenko, M. V., & Avramenko, D. O. (2025). Vplyv alhorytmiv rekomendatsii sotsialnykh merezh na informatsiini bulbashky. [The impact of social media recommendation algorithms on information bubbles.] Visnyk Natsionalnoho universytetu oborony Ukrainy. https://doi.org/10.33099/2617-6858–25–83–1–7-15 (in Ukranian)
- Pocheptsov, H. (2015). Suchasni informatsiini viiny. [Modern information wars.] Kyiv: Vydavnychyi dim «Kyievo-Mohylianska akademiia». (in Ukranian)
- Barrera, D. (2020). Crisis informatics in the context of social media crisis communication: Theoretical models, taxonomy and open issues. IEEE Access, 8, 182236–182260. https://doi.org/10.1109/ACCESS.2020.3030184
- Berger, T. (2022). The echo chamber-driven polarization on social media. Journal of Student Research, 12(4), 1–7. https://doi.org/10.47611/jsr.v12i4.2274
- Chaplak, Y., Chuyko, H., & Andrieieva, Y. (2023). Psychological aspects of the influence of information bubbles on individuals and society. Psychological Journal, 9(5), 38–51. https://doi.org/10.31108/1.2023.9.5
- Difranzo, D., & Gloria-Garcia, K. (2017). Filter bubbles and fake news. XRDS: Crossroads, The ACM Magazine for Students, 23(3), 32–35. https://doi.org/10.1145/3055153
- Flaxman, S., Goel, S., & Rao, J. M. (2016). Filter bubbles, echo chambers, and online news consumption. Public Opinion Quarterly, 80(S1), 298–320. https://doi.org/10.1093/poq/nfw006
- Holone, H. (2016). The filter bubble and its effect on online personal health information. Croatian Medical Journal, 57(3), 298–301. https://doi.org/10.3325/cmj.2016.57.298
- Starbird, K., Arif, A., & Wilson, T. (2018). Ecosystem or echo-system? Exploring content sharing across alternative media domains. Proceedings of the International AAAI Conference on Web and Social Media, 12(1), 365–374. https://doi.org/10.1609/icwsm.v12i1.14998
- Pariser, E. (2011). The filter bubble: What the internet is hiding from you. Penguin Press.