- A graph-based algorithm is proposed for detecting song propagation patterns in Spotify.
- Nodes are countries and edges reflect the frequent flow of songs across them.
- The patterns are reflected in cultural components such as language or migration flows.
- Predictors of song propagation based on the discovered patterns are discussed.
Nowadays, music streaming services allow users to get instant access to an unprecedented amount of music of any type. This entails that songs, including potential new hits, can be discovered by listeners in any part of the globe and their propagation can be tracked through these streaming services. In this context, the present work focuses on recognizing the mobility patterns that songs follow in such a propagation among different countries of the world. To this end, this work defines a novel mechanism to uncover such mobility patterns of music from a directed-graph structure where nodes are countries and each edge reflects a frequent propagation of songs between pairs of countries. The resulting patterns reflect strong correlations with the migratory flows and the cultural and social similarities among regions. For instance, a propagation pattern was observed among North European countries with a good command of English. From such patterns, potential predictors for anticipating the mobility of a song are discussed. The results of this work can be beneficial for record companies and artists in their marketing campaigns for album releases and the organization of concerts and festivals.