Title: Assessing the Impact of Music Recommendation Diversity on Listeners

Supervisors: Dr. Emilia Gómez and Dr. Carlos Castillo

Jury: Dr. Christine Bauer (Utrecht University), Dr. Perfecto Herrera (UPF), Dr. Mounia Lalmas-Roelleke (Spotify)

Abstract: This thesis focuses on assessing the impact that music recommendation diversity may have on listeners. In the music domain, diversity is one of the values that recommender systems should preserve, because the world music heritage is a mixture of several artistic languages and sonic landscapes, and differences are at the heart of such processes of melting. However, a strain of critical studies has brought to light several issues due to the use of recommender systems, at the root of phenomena such as the exacerbation of the popularity bias, discrimination towards historically underrepresented groups in the music industry, or the reinforcement of homogenous listening habits. By exploring the measurement, perception and finally the impact of diversity, we discuss how favouring the exposure to diverse music, algorithmic recommendations may help people in understanding their musical Self by observing the “other” cultures with which they interact.

Video: https://youtu.be/H0Qm9cmWQ3k