Abstract
This is a case study of Spotify's related artist network of Dutch drum and bass artist Noisia, incorporating a critical perspective of data and streaming platforms, it argues that network theory can help deal with the deluge of online data by showing artists and music business professionals how to see relationships instead of mere isolated events. The case study applies network theory and methods within a datacritical context. Three core measures are employed to determine different kinds of powerful actors (as in artists on Spotify) in a particular network. The analysis uncovers how each actor is embedded in networked structures of relationships that provide opportunities, constraints, coalitions, and workarounds. The consequence of the network being algorithm-generated is also considered, as it was found that this creates a situation that differs from regular social networks.
Original language | English |
---|---|
Pages (from-to) | 67-101 |
Number of pages | 35 |
Journal | International Journal of Music Business Research |
Volume | 8 |
Issue number | 1 |
Publication status | Published - 1-Apr-2019 |
Event | Vienna Music Business Research Days - University of Music and Performing Arts, Vienna, Austria Duration: 12-Sep-2018 → 14-Sep-2018 https://musicbusinessresearch.wordpress.com/ |
Keywords
- networks and graphs
- music
- Spotify
- Socio-technical systems
- Network analysis