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The Impact of Algorithms on Music Consumption: a systematic literature review

Signos do Consumo




Recommender Systems (SR) are defined as algorithms that classify and recommend cultural products based on data on user practices and behavior. The purpose of this article is to diagnose the social and cultural consequences of music recommendation algorithms as online cultural intermediaries, examining how and to what extent they affect cultural perception, music classification, taste formation, listener behavior and user choices.


We carried out a systematic literature review to identify and discuss scientific production on the social and cultural implications of such algorithms in music consumption practices. 311 articles were obtained from bibliographic searches in nine different scientific databases.


Our critical analysis indicated four main thematic approaches explored by the scientific community on this topic between 2000 and 2016: 1) The role of recommendation systems in the music industry; 2) Impact of streaming services on music downloads; 3) Bias in rating and recommendation of content; and 4) Music consumption as a social resource.


The results reveal the logic of cultural intermediation via recommendation systems in the music market: these algorithms influence, model and map users' tastes and habits in an apparently free, diverse and at the same time personalized environment.


 

How to cite: SANTINI, Rose Marie; SALLES, Debora. O impacto dos algoritmos no consumo de música uma revisão sistemática de literatura. Signos do Consumo, v. 12, n. 1, p. 83-93, 2020.


O Impacto dos Algoritmos no Consumo de Música - uma revisão sistemática de literatura
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