The impact of algorithms on music consumption

a systematic literature review

Abstract

Recommendation Systems (RS) are defined as algorithms that classify and recommend cultural products based on data about users’ practices and behavior. The purpose of this research 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 conducted a systematic literature review to identify and discuss the 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 download; 3) Bias in the classification and recommendation of content; and 4) Consumption of music 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 the tastes and habits of users in an apparently free, diverse and personalized environment.