Music Genres Reconsidered: Challenging Established Genres with a Data-driven Approach
dc.contributor.author | Hotz-Behofsits, Christian | |
dc.contributor.author | Winkler, Daniel | |
dc.contributor.author | Wlömert, Nils | |
dc.date.accessioned | 2021-12-24T17:48:51Z | |
dc.date.available | 2021-12-24T17:48:51Z | |
dc.date.issued | 2022-01-04 | |
dc.description.abstract | Consumers widely use music genres (e.g., pop, rock) for finding the right products. However, they are commonly arbitrary, not-standardized, disputed, and closely related genres often overlap. In this paper, we challenge established music genres (e.g., pop, rock) by comparing them to an entirely data-driven approach. To this end, we use a unique data set of revealed user preferences to carry out a context-based artist similarity. This measure is used in turn to find high-density artist clusters. The contribution of this paper is twofold. First, we investigate the differences between established music genres and data-driven clustering. Second, we provide implications for researchers and practitioners. | |
dc.format.extent | 8 pages | |
dc.identifier.doi | 10.24251/HICSS.2022.412 | |
dc.identifier.isbn | 978-0-9981331-5-7 | |
dc.identifier.uri | http://hdl.handle.net/10125/79746 | |
dc.language.iso | eng | |
dc.relation.ispartof | Proceedings of the 55th Hawaii International Conference on System Sciences | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | |
dc.subject | Streaming Media in Entertainment | |
dc.subject | clustering | |
dc.subject | consumer preferences | |
dc.subject | music genres | |
dc.subject | product discovery | |
dc.subject | product similarity | |
dc.title | Music Genres Reconsidered: Challenging Established Genres with a Data-driven Approach | |
dc.type.dcmi | text |
Files
Original bundle
1 - 1 of 1