Algorithmic Filtering and Social Polarization
DOI:
https://doi.org/10.5281/zenodo.17492988Ключевые слова:
algorithmic filtering, echo chambers, social polarization, social media, collective thinking, information exposure, online behaviorАннотация
This article examines the impact of algorithmic filtering on social media platforms and its influence on users’
perspectives and collective thinking. Algorithmic systems, which curate content based on user preferences, browsing
history, and online behavior, often create “echo chambers” – environments where individuals are primarily exposed to
information that aligns with their existing beliefs. As a result, users may become increasingly insulated from alternative
viewpoints, reinforcing preexisting opinions and contributing to social polarization. The study highlights the significant
implications of algorithmic filtering for both individual cognition and group dynamics. By shaping the information users
encounter, algorithms can influence political, social, and cultural attitudes while also affecting critical thinking, empathy,
and engagement with diverse perspectives. The findings further suggest that understanding the relationship between
algorithmic recommendations and social integration is essential for developing strategies to foster a more balanced,
inclusive, and critically engaged online environment.
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