Litcius/Paper detail

Detecting collaboration profiles in success-based music genre networks

Gabriel P. Oliveira, Mariana Santos, Danilo B. Seufitelli, Anísio Lacerda, Mirella M. Moro

2020Zenodo (CERN European Organization for Nuclear Research)19 citationsDOIOpen Access PDF

Abstract

We analyze and identify collaboration profiles in success-based music genre networks. Such networks are built upon data recently collected from both global and regional Spotify weekly charts. Overall, our findings reveal an increase in the number of distinct successful genres from high-potential markets, pointing out that local repertoire is more important than ever on building the global music ecosystem. We also detect collaboration patterns mapped into four different profiles: Solid, Regular, Bridge and Emerging, wherein the two first depict higher average success. These findings indicate great opportunities for the music industry by revealing the driving power of inter-genre collaborations within regional and global markets.

Topics & Concepts

RepertoireBridge (graph theory)Computer scienceMusic industryData scienceWorld Wide WebSociologyAcousticsMedicineInternal medicinePhysicsPedagogyMusic educationMusic and Audio ProcessingMusic Technology and Sound StudiesComplex Network Analysis Techniques
Detecting collaboration profiles in success-based music genre networks | Litcius