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Knees, P. (2019). On Stakeholders and Data Biases in Music Recommendation. Media Technology and Interaction Design Seminar, KTH Stockholm, Sweden. http://hdl.handle.net/20.500.12708/87011
Music recommenders have become a commodity for music listeners. They drive manifold personalized services such as music discovery and activity-based playlisting. In practice, the task of music recommendation is a multi-faceted task, serving multiple stakeholders. Besides the music listener and the publishers of the music, the service itself as well as other branches of the music industry are affec...
Music recommenders have become a commodity for music listeners. They drive manifold personalized services such as music discovery and activity-based playlisting. In practice, the task of music recommendation is a multi-faceted task, serving multiple stakeholders. Besides the music listener and the publishers of the music, the service itself as well as other branches of the music industry are affected. In this talk, I will discuss the multiple aspects and stakeholders present in the process of music recommendation. I will further discuss possible impacts on academic research in this area, foremost regarding the question of potential biases in datasets and illustrate aspects that should be taken into consideration when developing music recommender systems.
