Community Detection of Singers in Spotify Rock Playlists Using Louvain Method

Abstract

Spotify is one of the leading music streaming platforms, allowing users to create playlists and select songs based on their preferences. Rock music has remained a prominent genre on Spotify, especially in Indonesia, where it holds historical and cultural significance and serves as a medium for social and political expression. This study investigates how user preferences shape the network structure among Indonesian rock artists. Using the Louvain community detection method, artists were grouped based on their co-occurrence in playlists to uncover community patterns within the genre. Data were collected by scraping playlists using the keyword “Rock Indonesia.” The optimal configuration was found with a k-core value of 3 and an edge weight threshold of 0.39, resulting in a modularity score of 0.4782. Three main communities were identified, differentiated by subgenre, active period, and record label.