Culture Unbound: Journal of Current Cultural Research (Jul 2022)
Does Spotify Create Attachment?
Abstract
This paper seeks to measure the extent to which algorithmically generated playlists, conceptualised herein as cultural intermediaries (Bourdieu 1984), create ‘attachment’ between consumers of music and producers of music. This was undertaken following debates in the professional music press problematising the ability of streaming platforms to create relationships between artists and listeners and, in a wider discussion, to generate sustainable income for musicians (Chartmetric 2018, Mulligan 2019 in Griffiths 2019, Music Ally 2019). We develop the idea from cultural and economic scholars that intermediation results in ‘attachment’ on behalf of consumers (Callon et.al 2002, Smith Maguire & Matthews 2012) by formulating a definition of the term informed by insights from consumer psychology and applying this framework to a 115-question survey completed by listeners to Spotify’s ‘Discover Weekly’ Playlist for a one-week period. The findings suggest that the playlist was able to generate close to no attachment for those considered poorly-involved new music consumers, and only minor to mid-levels of attachment for those participants considered heavily-involved new music consumers. We therefore propose that algorithmically curated playlists can influence low-cost audience attachment behaviours while their overall impact on the economic success of artists may be limited. This paper contributes towards academic debates concerning the role and impact of cultural intermediaries and lends early empirical support to discussions within the professional music industries and wider public policy (GOV 2020) concerning the uncertain ability of playlists to influence the artist-fan relationship. In addition, by developing a methodologically precise definition of ‘attachment’, it is hoped that the framework provided by this modest study can act as a guide for other researchers to explore the concept of intermediation and attachment with larger sample sizes on alternative playlist types and on other digital platforms.
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