Understanding Echo Chambers in Recommender Systems: A Systematic Review

Echo chambers refer to the phenomenon in which individuals are consistently exposed to content that aligns with their existing viewpoints. Over time, this can narrow a user’s perspective and make it harder to encounter different opinions. In this systematic literature review, we looked at studies published between 2019 and early 2025 and how they have approached this issue, from understanding the cause, and examining existing detection and mitigation strategies. We went through and organized the main findings, noting patterns in the algorithms used, the role of user behavior, and the influence of the data itself. Several works also suggest ways to introduce more variety into recommendations, aiming to break repetitive exposure. Our review confirms that echo chambers and filter bubbles do exist in recommender systems and that they raise concerns for diversity and fairness. Furthermore, we end by pointing to open questions and possible directions for future work, for both researchers and practitioners.