Exploring Music Diversity Needs Across Countries

Abstract

Providing diversity in recommendations has shown to positively influence the user's subjective evaluations such as satisfaction. However, it is often unknown how much diversity a recommendation set needs to consist of. In this work, we explored how music users of Last.fm apply diversity in their listening behavior. We analyzed a dataset with the music listening history of 53,309 Last.fm users capturing their total listening events until August 2014. We complemented this dataset with The Echo Nest features and Hofstede's cultural dimensions to explore how music diversity is applied across countries. Between 47 countries, we found distinct relationships between the cultural dimensions and music diversity variables. These results suggest that different country-based diversity measurements should be considered when applied to a recommendation set in order to maximize the user's subjective evaluations. The country-based relationships also provide opportunities for recommender systems to personalize experiences when user data is limited by being able to rely on the user's demographics.