Exploiting Sequential Music Preferences via Optimisation-Based Sequencing
Dmitrii Moor, Yi Yuan, Rishabh Mehrotra, Zhenwen Dai, Mounia Lalmas
Digital media platforms give users access to enormous amounts of content. To stay interested in this content, users must explore by seeking variety. In this study, we examine how users explore online content on Spotify at different points of their lifecycles, whether by discovering entirely novel music or by refreshing their listening habits from one time frame to the next. We find clear differences between users at different points of their off-platform lifecycles, with younger listeners consistently exploring less and exploiting known content more. Across their on-platform histories, users also explore in uneven patterns by following seasonal cycles and exploratory phases. Additionally, we contrast exploration with taste diversity and find that these concepts are surprisingly distinct. Through this large-scale, observational study of exploration, our work clarifies how users encounter and cycle through heterogeneous content at various stages of their lifecycle.
Dmitrii Moor, Yi Yuan, Rishabh Mehrotra, Zhenwen Dai, Mounia Lalmas
Thomas McDonald, Lucas Maystre, Mounia Lalmas, Daniel Russo, Kamil Ciosek
Federico Tomasi, Joseph Cauteruccio, Surya Kanoria, Kamil Ciosek, Matteo Rinaldi, Zhenwen Dai