Crafting online identities: Active and reflexive identity work on Spotify

Abstract

The development of on-demand music streaming platforms, such as Spotify, Apple Music and Pandora, have transformed the dissemination and consumption of music. These networks provide open forums for listening, sharing, rating and recommending music. They have the ability to shape music consumption in ways not previously encountered. These online music streaming services not only offer instant, ubiquitous access to vast catalogues of music, but they also have the potential to influence what music users listen to and the ways they consume it. By collecting a vast amount of user data on music choices, listening habits and interactions, computational techniques, in the form of recommendation algorithms, can recognise and predict the similarities and differences in musical preferences of an entire user database. These recommender algorithms help structure the large and diverse array of possible song choices, but they also have the ability to influence the music that individuals are and are not presented with on an increasingly personalised basis.
Music has traditionally served as a powerful resource for identity work, allowing individuals to construct, manage and perform who they are and who they want to be. What do these online music streaming platforms with integrated recommendation systems mean for our identity work? Do they have the potential to shape our identities as they do our music consumption? Drawing ona mixed methods approach and focusing on Spotify, the market leading music streaming service in the UK, this thesis contributes to existing scholarship on music consumption in an online context. Extending current knowledge, primary research focuses on users to explore how music streaming platforms can enable the effective construction and performance of online identities. Through the triangulation of online survey responses, online observation and semi-structured interviews, I investigate the types of identity work achieved through feelings of psychological ownership, the curation of online music libraries, playlists and public and private streaming choices. Spotify also has the potential to shape identity work. A diverse array of data points collected during engagement with the platform become reassembled into what Haggerty and Ericson (2000) refer to as ‘data doubles’. These data doubles are perceived as online mirrors to human identity that are subsequently used to determine the music choices that users are and, perhaps more importantly, are not presented with.
The research contributions that this thesis makes are highly important considering the modern world we live in today, where qualitative, non-numeric aspects of daily life are increasingly becoming datafied, smart devices are ubiquitous and always-on mobile Internet access is prevalent. This thesis therefore sheds light on the role of the platform and its technologies in crafting online identities, exploring how Spotify attempts to reflect a user’s identity through profile construction and personalised recommendations. It considers how processes of self fashioning through music can be mediated and shaped by the technology of recommender systems. These platforms do not only reflect user identity. Unlike much of the existing literature in data studies, which addresses concerns over online surveillance and algorithmic control, this thesis presents users as data activists who appropriate platform affordances and adapt them to their benefit. This research therefore explores the power and agency exerted by both the user and the system. Understanding this reciprocal relationship allows for new insights into online identity work.

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Identifiers

ORCID for Christophe Mues: orcid.org/0000-0002-6289-5490

ORCID for Silke Roth: orcid.org/0000-0002-8760-0505

ORCID for Laurie Stras: orcid.org/0000-0002-0129-2047

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