Recommender systems, representativeness, and online music: A psychosocial analysis of Italian listeners

Recommender systems shape music listening worldwide due to their widespread adoption in online platforms. Growing concerns about representational harms that these systems may cause are nowadays part of the scientific and public debate, wherein music listener perspectives are oftentimes reported and discussed from a cognitive-behaviorism perspective, but rarely contextualised under a psychosocial and cultural lens. We proceed in this direction, by interviewing a group of Italian music listeners and analysing their narratives through Emotional Textual Analysis. Thanks to this, we identify shared cultural repertoires that reveal people's complex relationship with listening practices: even when familiar with online platforms, listeners may still lack a critical understanding of recommender systems. Moreover, representational issues, particularly gender disparities, seem not yet fully grasped in the context of online music listening. This study underscores the need for interdisciplinary research to address representational harms, and the role of algorithmic awareness and digital literacy in developing trustworthy recommender systems.