Mining the Dynamics of Music Preferences from a Social Networking Site

In this paper we present an application of our incre-mental graph clustering algorithm (DENGRAPH) on a data set obtained from the music community site Last.fm. The aim of our study is to determine the music prefer-ences of people and to observe how the taste in music changes over time. Over a period of 130 weeks, we ex-tract for each interval user profiles of 1,800 users that represent their music listening behavior. By building and incrementally clustering a graph of similar users, we ob-tain groups of people with similar music preferences. We label these clusters with genres according to the user profiles of the cluster members. Due to the incremen-tal nature of DENGRAPH we show how clusters evolve over time. Besides the growth and decrease of clusters we observe how new clusters emerge and old clusters die. Furthermore, we show the merge and split of clus-ters. The results of our experiments indicate that DEN-GRAPH is particularly useful to efficiently detect groups of similar users and to track them over time.