Mining Culture-Specific Music Listening Behavior from Social Media Data

Incorporating user characteristics and contextual information has shown to be essential when it comes to personalized music retrieval and recommendation. To this end, the current location of a user is often exploited. However, relying solely on GPS coordinates neglects the cultural background of users, which does not necessarily coincide with political borders. In this paper, we analyze culture-specific music listening behavior based on a dataset of 2,724 Spotify users, 62,104 distinct tracks and 104,390 listening events by modeling users jointly via their musical preferences and cultural characteristics. By applying a density-based spatial clustering algorithm, we identify nine clusters which reflect similar users regarding both their musical preference and cultural background. Our findings show that cultural aspects cannot be approximated by GPS coordinates and that incorporating cultural characteristics allows for more precise user characterization. Also, we observe that listening patterns occur on two different levels: we observe country-specific listening patterns as well as cross-country listening patterns that span across several countries.