Algorithmic Media as a Factor of Epistemic Fragmentation: The Formation of Information Bubbles and the Influence on Public Opinion in the Context of Digital and Hybrid Conflicts

S. Belkova

Abstract


The aim of this study is to conduct a comprehensive analysis of algorithmic media as a factor in the epistemic fragmentation of society and to determine their impact on public opinion in the context of the digital environment and hybrid conflicts.

Research methodology. The study uses a systemic approach to the analysis of algorithmic media as complex information ecosystems; comparative analysis to compare theoretical concepts of digital communication; synthesis and generalization of empirical research to identify patterns in the functioning of information bubbles; and an interdisciplinary approach as a methodological basis that ensures the integration of knowledge from media studies, sociology, and cognitive science.

The results indicate that algorithmic systems create personalized information environments that contribute to the emergence of information bubbles and echo chambers. A three-level nature of this process (algorithmic, behavioral, and cognitive) has been demonstrated.

The novelty lies in the theoretical refinement of the concept of epistemic fragmentation in the context of algorithmic media, the substantiation of epistemic asymmetry as a structural effect of digital information systems, as well as in generalizing the interaction of algorithmic, cognitive, and social mechanisms in the formation of information bubbles.

The practical significance of the research results lies in using the results to develop media literacy and information security.

Key words: algorithmic media, filter bubbles, echo chambers, epistemic fragmentation, public opinion, digital polarization, misinformation, social media.

References


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DOI: http://dx.doi.org/10.32840/cpu2219-8741/2025.4(64).1

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