If Spotify recommends Taylor Swift to me one more time, I might start believing it knows something about me that I don’t. It’s strange how a platform can make you question your own musical identity, even if you, like me, have never listened to T. Swizzle. Perhaps she and Westside Gunn have more in common than I thought, or perhaps there are assumptions even my own listening choices cannot defy.
Genre as Culture on Spotify
Spotify may be a useful site for finding music and creating playlists, but it is also important for examining how genre and identity are produced today. In looking at how Spotify organizes genre and distributes listening statistics, as discussed in Muchitsch & Werner’s paper, we can understand genre not simply as a descriptive category but as a system of representation that shapes how listeners come to understand themselves. Genre formation has long been recognized as unstable — “fleeting processes whose boundaries are permeable and fluctuating, yet nevertheless culturally and socially safeguarded” (Brackett, 2016 qtd. in Muchitsch & Werner, 2024, p. 306). Genres constantly shift and divide, giving rise to newer sub-genres like indie pop or bubble grunge. But genre is also representational; it defines a type of music and, by extension, a type of listener.
Metadata and Identity
Spotify’s use of genre as metadata allows us to better see how they construct identities — genre becomes an identity category embedded into algorithmic logic, a technical shorthand for grouping users and predicting their future behavior. Besides recommendations, the advent of personalized playlists — like the well-known (and awful) “Just For You”s — are examples of how technology actively dictates the media we encounter. The algorithm assumes an identity about the listener and continually supplies content that reinforces that assumption. Although it appears that our listening habits inform the algorithm, the relationship is indeed reciprocal. Technology also shapes our perceptions of our own identities by offering back a curated and often reductive portrait of who we “are” as listeners.
Bollmer and Performativity
This feedback loop often goes unnoticed because of the widespread belief that technologies are neutral. Bollmer’s work on representation, identity, and performativity challenges this assumption, reminding us that representational identities—such as those produced in digital platforms—affect our capacity to act and perform within society. Especially as branding culture dominates the media landscape, individuals frequently become the “faces” of genres, embodying particular aesthetics or attitudes. These stylized identities influence how other listeners understand themselves and how the algorithm categorizes them in return. And, as we know but will not explore fully here, these categorizations are far from unbiased.
For Bollmer, identity is something both enacted and mediated. We cannot fully control how we are represented, nor can we detach ourselves from the biases and conditions that shape how we perform in the world. At the same time, we are constantly surrounded by stimuli that instruct us in the ways we should construct our identities. Playlists and music taste are only slim examples of the performative acts through which we present and negotiate a sense of self. Spotify, by mediating genre, participates in this process, co-producing musical identity through representational systems that determine what counts as meaningful performance.
What does this mean for users?
Rather than stable categories, genres have become interfaces for identity. Users construct self-image through listening habits, while platforms translate those habits into data profiles that feed back into the listening experience. Mood playlists—“chill,” “in love,” “rainy day,” “main character”—make this even clearer. They frame music not only as sound, but as a tool for managing and performing the self. In this way, Spotify exemplifies how contemporary media systems blur the lines between what we choose and what is chosen for us, shaping identity through the very categories that claim to represent it.
Identity as “Self Work”
Tia DeNora’s idea of music as a “technology of the self” deepens this understanding of genre and identity. For DeNora, people use music to regulate emotion, construct moods, and shape situations—music is a tool for self-presentation and self-maintenance. But when platforms pre-organize music into specific categories, they intervene in this process, prescribing what kinds of selves the listener might want to inhabit. What once felt like personal, intuitive self-work becomes filtered through Spotify’s mood-based playlists, quietly guiding the identities we perform and the emotions we deem appropriate.
Implications
The implications of this are subtle but significant; If identity is enacted through musical choice—as Bollmer and DeNora both suggest—then algorithmic curation narrows the range of performative possibilities. The listener performs the self through their music, but the platform anticipates, predicts, and nudges that performance, creating a closed loop where identity is both expressed and engineered. Genre, once a loose cultural concept, becomes a data-driven identity label that platforms use to categorize and influence behavior. And because these systems appear neutral, the shaping of identity through recommendations often feels natural rather than infrastructural.
In the end, the relationship between genre, identity, and streaming platforms reveals far more than how music is organized—it shows how contemporary technologies dictate who we are allowed to become. Spotify doesn’t just categorize sound; it categorizes people, returning our listening habits to us as ready-made portraits of taste and selfhood. Between Bollmer’s emphasis on mediated identity and DeNora’s conception of music as self-shaping, it becomes clear that our musical preferences are never solely our own. They emerge from an ongoing negotiation between personal expression and platform governance. And if my “rap-only” listening history can still make Spotify insist I’m a Taylor Swift fan, it’s worth asking: are we using these systems to express ourselves, or are they teaching us who we ought to be?
Bollmer, Grant. Materialist Media Theory. Bloomsbury Publishing USA, 2019.—Introduction.
DeNora, Tia. “Music as a Technology of the Self.” Poetics, vol. 27, no. 1, 1999, pp. 31–56.
Muchitsch, Veronika, and Ann Werner. “The Mediation of Genre, Identity, and Difference in Contemporary (Popular) Music Streaming.” Popular Music and Society, 2024, pp. 302-328.
Written by Allie Demetrick
Photo from Spotify
So interesting! I love exploring how music genres are intertwined with identity. It’s always intrigued me how many subcultures are defined by the music they listen to, like emo, punk, or hiphop.
I’ve seen some online discourse describing how TikTok and other contemporary mass media is homogenising these subcultures and reducing them to “aesthetics” and “cores”. Take boho style, visually similar to hippie, yet it lacks the lifestyle and political rebellion that was intertwined with hippie style. Perhaps it could be argued that this redefinition is an expansion of these subcultures. I’m curious if you think that Spotify encourages this phenomenon as well?
YES, absolutely Spotify is really jumping on this trend, particularly with mood and activity based playlists! “Genre” is no longer simply technical, but is now participating in new organization and exploration of genre as further identity-based. Moreover, Spotify uses the language of users without an understanding of the context; much like the boho that you’re describing, identities are separated from their material and physical qualities that originally identified them — like the hippie movement of the 70s.
I love the contemporary context that this post is situated in — I too am victim of Spotify’s seemingly irrelevant T. Swift recommendations. I love your commentary on how genre has become intertwined with interface and subsequently our identity, and Muchitsch, Veronika, and Ann Werner’s observations on how music has recently been categorized more by mood and situation than classic sound is an interesting lens to analyze how our taste in media has changed. I would love to hear your thoughts on advertisements on Spotify, and how mega-artists like Taylor Swift being able to inject their songs into a playlist of any genre affects the media consumption experience and the world of music as a whole!
Oh it is so frustrating how many mega-artists weasel their way into my playlists, I am so glad you mentioned this! Spotify especially is good at subtle advertising, and perhaps not even in the way you think! Besides the clear “Merch” sections under artist profiles, the placement of artist’s song on places like the Home Page, or the recommended music at the bottom of a playlist is pushing forward specific individuals who stand for principles that Spotify agrees with, and can provide a personal brand identity strong enough to convince audiences that they are, in fact, NOT a brand identity. This is how our identities are affected (in part), and also how consumerist principles are injected into technology yet still remain mostly invisible to the public eye.
This is so interesting to read! I often find other music apps recommending me songs from genres that I have only liked for a short while and certainly does not make the most of my playlist. In fact the recommendations seem to be influenced by what is currently trending more than the user’s preference, as I often find new popular songs released recently gets recommended more frequently. Another subject I want to touch on when talking about algorithm-concluded identity vs. true human identity is AI chatting. I have experienced AI concluding some identities to the same ways of expressions, despite the evident difference between the character’s backgrounds and settings. Later I found that these ways of expression are most likely influenced by the user’s input. While this may be solved by technological evolutions, it does make me consider more about whether identity is expressed then concluded, or provided and influenced as well.
This is very interesting and incredibly reflective of my subject, thank you so much for such a great conclusion! We are seeing our own behaviours actively affect and effect technology, and your example of AI chatting (and even how Google categorizes ads from your searches) is a perfect picture of how useful it is for brands to place you (the user) within a box. Like how a doctor may diagnose you with the wrong disease because of the symptoms you express, algorithms and AI are not only profiting off of the collective categorization of individuals, they are profiting off of the instability you feel in an online space. There is no ground, nor a stable horizon — we are lost, searching for remnants of an identity that was never ours to begin with.
I’ll go through months where I listen almost exclusively to one or two genres, and then suddenly Spotify starts pushing very different and contrasting playlists based on identities like a “soft girl” playlist, and seeing those recommendations over and over, I sometimes catch myself wondering if that is really what I am O_O.
I realized how Spotify became an interface for curating my identity without noticing, and it’s very surprising to see what playlists and recommendations the algorithm comes up with, because it means my “taste” isn’t completely mine. It’s shaped by the algorithm that sees patterns I don’t, and sometimes tries to fit me into a version of myself I never directly chose.
Precisely! “Taste” has always been about belonging within a certain social circle, and with the integration of suggestive systems (like Spotify’s algorithm), I wonder to what circle we are being drawn towards? I can’t help but feel this pushes the narrative of a capitalistic, collective fantasy of inclusion that doesn’t in fact reduce the isolation of outgroups (“Distastefuls”), but increasingly produces it.
Hi! I really enjoyed your post! Your discussion of Spotify as a site where genre, identity, and algorithmic logic intersect was really insightful. I liked how you emphasized that genre isn’t just a label but a representational system that shapes how listeners understand themselves, and how playlists and mood-based categories guide identity performance. Your point about the reciprocal feedback loop between user behavior and platform recommendations made me think about how much of our musical “self-expression” is actually curated by the system. I also appreciated how you tied Bollmer and DeNora together, showing how music functions as both self-work and mediated identity. It makes me wonder how much of our taste is truly personal versus algorithmically nudged, and whether users can reclaim agency over these curated identities.
I really enjoyed this and it made me think about how often we let platforms tell us who we are without even noticing. One thing I wanted to ask is whether you think people ever push back against the identities Spotify assigns them, or if most listeners just accept the portrait the algorithm hands them. I was also curious about your take on mood playlists. Do you think they genuinely help people express a feeling, or do they end up telling people what feelings they are supposed to have in the first place.