Music Genres Reconsidered: Challenging Established Genres with a Data-driven Approach
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2022-01-04
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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.
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Streaming Media in Entertainment, clustering, consumer preferences, music genres, product discovery, product similarity
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8 pages
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Proceedings of the 55th Hawaii International Conference on System Sciences
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Attribution-NonCommercial-NoDerivatives 4.0 International
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