Assess the Evidence for and Against the Existence of ‘Filter Bubbles’
DOI:
https://doi.org/10.62051/ijsspa.v8n3.02Keywords:
Filter Bubbles, Algorithmic Personalization, Information Diversity, Confirmation BiasAbstract
This paper critically assesses the evidence for and against the existence of "filter bubbles"-a phenomenon where algorithmic personalization limits users’ exposure to diverse information. Drawing on theoretical discussions and empirical studies, the paper explores how user behavior, platform algorithms, and business models contribute to the formation of filter bubbles. While personalization can enhance user experience, it may also reinforce confirmation bias and lead to ideological homogeneity, particularly in political contexts. However, opposing views highlight the lack of consensus on definitions and insufficient empirical support for widespread filter bubble effects. The study concludes that although filter bubbles exist, their impact varies across platforms and users. Active user behavior and cross-platform engagement can mitigate negative consequences, suggesting that filter bubbles are not inevitable or irreversible.
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