We present a study of the relationship between music genres and graph-related metrics in a directed graph of music credits built using data from Spotify. Our objective is to examine crediting patterns and their dependence on music genre and artist popularity. To this end, we introduce a node-wise index of reciprocity, which could be a useful feature in recommendation systems. We argue that reciprocity allows distinguishing between the two types of connections: citations and collaborations. Previous works analyse only undirected graphs of credits, making the assumption that every credit implies a collaboration. However, this discards all information about reciprocity. To avoid this oversimplification, we define a directed graph. We show that, as previously found, the most central artists in the network are classical and hip-hop artists. Then, we analyse the reciprocity of artists to demonstrate that the high centrality of the two groups is the result of two different phenomena. Classical artists have low reciprocity and most of their connections are attributable to citations, while hip-hop artists have high reciprocity and most of their connections are true collaborations.

Citation is not Collaboration: Music-Genre Dependence of Graph-Related Metrics in a Music Credits Network / G. Clerici, M. Tiraboschi - In: Proceedings of the 20th Sound and Music Computing / [a cura di] R. Bresin, K. Falkenberg. - Stockholm : Royal College of Music and KTH Royal Institute of Technology, 2023 Jun 14. - ISBN 978-91-527-7372-7. - pp. 317-322 (( Intervento presentato al 20. convegno Sound and Music Computing Conference tenutosi a Stockholm nel 2023.

Citation is not Collaboration: Music-Genre Dependence of Graph-Related Metrics in a Music Credits Network

G. Clerici
Primo
;
M. Tiraboschi
Ultimo
2023

Abstract

We present a study of the relationship between music genres and graph-related metrics in a directed graph of music credits built using data from Spotify. Our objective is to examine crediting patterns and their dependence on music genre and artist popularity. To this end, we introduce a node-wise index of reciprocity, which could be a useful feature in recommendation systems. We argue that reciprocity allows distinguishing between the two types of connections: citations and collaborations. Previous works analyse only undirected graphs of credits, making the assumption that every credit implies a collaboration. However, this discards all information about reciprocity. To avoid this oversimplification, we define a directed graph. We show that, as previously found, the most central artists in the network are classical and hip-hop artists. Then, we analyse the reciprocity of artists to demonstrate that the high centrality of the two groups is the result of two different phenomena. Classical artists have low reciprocity and most of their connections are attributable to citations, while hip-hop artists have high reciprocity and most of their connections are true collaborations.
music; genres; graph; centrality; collaboration; citation; musicology; reciprocity
Settore INF/01 - Informatica
14-giu-2023
KMH Royal College of Music
KTH Royal Institute of Technology
https://zenodo.org/record/8136568
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/997649
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