Music Listening Practices Directed by Algorithms: Discussing Personalized Playlists in the Context of Pseudo Individualization

Abstract

In this study the personalized playlists of digital music media based on algorithms will be examined specifically for Deezer, and the features of these lists such as “freedom” and “personalized” will tried to be understood. The new media not only has provided convenience and affordability to the audience, but also affected the production, distribution and consumption processes of music and the functioning of the commercial music industry. Digital music media, which has become the main music listening tool today hosting many and different genres of music and providing an easy and inexpensive music listening experience to the listener, transform into priority areas where many musicians from different localities will bring their music into circulation with similar motivations. While this situation paves the way for the freedom of the audience among many options, according to some opinions, with a different perspective it causes a listener profile that does not know what to listen to among millions of songs and becomes open to direction. Personal playlists using artificial intelligence technologies and algorithms are depicted by these platforms as guide for the unstable listeners. The suspicion of musicians, listeners and broadcasters in this guiding state causes us to question the "personal" status of personalized playlists and in direction of ethnomusicology discipline which makes inferences in line with field data, causes us to reopen certain elements of the cultural industry paradigm that has been reached. In the study, personalized playlists of digital music media based on algorithms are examined specifically for Deezer and explained with fieldwork data. The suspicion of the "freedom" and "personal characteristics" of these lists is conveyed by the specific parameters of the culture industry and the pseudo individualization.