Abstract
Music streaming platforms have changed consumption modes through recommender systems and personalized deliveries. On Twitter/X, we observed listeners talking about teaching these systems in order to increase their accuracy in relation to their own tastes. We mapped these socio-communicational practices with the aim of investigating what they mean by educating algorithms and how these reports express taste performances. Using the collection and analysis of the contents of publications made by listeners as a methodology, the study is based on 82 tweets/xs posted between 2021 and 2022. In them, we identified three axes of meaning: (1) pragmatic management of behaviors based on the idea of education; (2) transformations in musical consumption; and (3)performances of a taught taste. As results, we propose the notion of algorithmic educability, which points to the naturalization of data-driven listening.
Keywords
music streaming platforms; education; algorithms; taste performance; Twitter/X