What is a "musical world"? An affinity propagation approach

This work proposes a method based on the affinity propagation clustering technique to classify artists and find representative artists for each musical category ("musical world") using only the listening history log of a music service. Two variants of the proposed method are compared with a classic k-means clustering approach and an evaluation based on folksonomy analysis is provided. The results suggest that affinity propagation is highly effective in the music domain, allowing for better classification of artists than classic clustering techniques. Furthermore, an analysis of the results indicates that classifying music by genres, even using more than one genre for each artist, is sometimes an oversimplification of the dynamics that govern the music ecosystem. While most of the clusters found have a strict relationship with a music genre, the characterization of some of the emerged "musical worlds" is related to other aspects like the geographic origin of the artists, the prominent themes in the lyrics, the evocative potential and the association with a culture/lifestyle or the context in which the music has been used.