Studying collaboration in music is a prominent area of research in fields such as cultural studies, history, and musicology. For scholars interested in studying collaboration, network analysis has proven to be a viable methodological approach. Yet, a challenge is that heterogeneous data makes it difficult to study collaboration networks across music genres, which means that there are almost only studies on individual genres. To solve this problem, we propose a generalizable approach to studying the topological properties of music collaboration networks within and between genres that relies on data from the freely available Discogs database. To illustrate the approach, we provide a comparison of the genres Jazz and Hip Hop.
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:91686 |
| Date | 29 May 2024 |
| Creators | Burghardt, Manuel, Gienapp, Lukas, Kruckenberg, Clara |
| Publisher | The Alliance of Digital Humanities Organizations and The Association for Computers and the Humanities |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/publishedVersion, doc-type:article, info:eu-repo/semantics/article, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | 1938-4122 |
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