Exploring the relationship between listener receptivity and source of music recommendations

Vargheese, John Paul; Wilson, Marianne; Stephen, Katherine; Salzano, Rachel; Brazier, David

Abstract

Music recommender systems are utilised by many music streaming platforms to provide new artist and song recommendations on a person-alised basis to listeners. By applying dynamic data modelling techniques, music recommender systems add to the current ecosystem of music recommendations. This includes direct and indirect, such as word of mouth, musical journalism, TV, radio, and live events. We report results from a study designed to investigate listener receptivity to music recommender systems, compared to editorial and peer based recommendations. Our results suggest participants' self-reported receptivity is significantly greater for music recommender systems compared to editorial and peer based. However, results from participants' evaluation of playlists perceived to be created by each recommender source suggests a significantly greater duration of play for peer-based recommendation playlists. No difference was found in likelihood to spend time or money on artists when only the recommendation source was considered. We discuss these results in relation to how anchoring bias may influence listeners' behaviours and how platform design may be informed based on their requirements and objectives.

Citation

Vargheese, J. P., Wilson, M., Stephen, K., Salzano, R., & Brazier, D. (2025, April). Exploring the relationship between listener receptivity and source of music recommendations. Presented at The 47th European Conference on Information Retrieval, Lucca, Tuscany

• Presentation Conference Type: Conference Paper (published)
• Conference Name: The 47th European Conference on Information Retrieval
• Start Date: Apr 6, 2025
• End Date: Apr 10, 2025
• Acceptance Date: Jan 17, 2025
• Deposit Date: Feb 21, 2025
• Publisher: Springer
• Peer Reviewed: Peer Reviewed
• Series Title: Lecture Notes in Computer Science
• Book Title: Advances in Information Retrieval
• Keywords: User evaluation, User receptivity, Recommender systems
• Public URL: http://researchrepository.napier.ac.uk/Output/4128110