Curating Christmas
Authors: Cole Sebastian , Robinson Jessica Yarin 
Published: November 2024

Introduction
As music listening transitions from physical to digital formats, the model for how people organise and discover new music is being taken over by the features of digital streaming services (Lüders; Rothenbuhler; Wikström). Playlists, akin to the mixtape of the analogue era, have broken up the album model, catering to specific moods, genres, and events (Bonini and Gandini; Prey; Siles et al., "Genres"). On Spotify, algorithmic playlists are readily mixed in with human-curated playlists, blurring the lines between the selections of personal human choice, and the datafied choices driven by computational algorithms and commercial influences (Prey; Seaver).
In this article, we take up the question of real vs. artificial in music curation through an exploratory investigation of Christmas music playlists in Norway. This investigation came about through a larger project on music streaming (Cole). We observed that, despite wide taste differences between participants, many of them had created playlists around the theme of Christmas. Christmas music, while often criticised for its commercialisation and perceived lack of authenticity, has been theorised by scholars to have an important role both in personal, autobiographical nostalgia and in building collective identity (Whiteley; Jarman-Ivens), particularly in the Nordic region (Hebert et al.; Lundmark; Schiermer and Carlsen).
Placing Christmas music at the intersection of user and algorithmic curation, we combine data from Spotify interviewees with data from Spotify’s API. By mapping the playlists into networks, we are able to identify songs and artists that are important connectors. We find that even in this largely formulaic and homogenous genre, the users employed playlists as a form of self-expression and individuality. Yet unexpectedly, the Spotify-created playlists may do more for linguistic preservation. Informed by interviews with Spotify users, we discuss “artificiality” in Spotify’s playlists, and consider how digital platforms mediate personal expression and collective identity.
The Rise of the Playlist            
One of the major disruptions of musical digitisation has been the breakup of the traditional album. Spotify, in particular, has pushed the organisation of music toward playlists (Prey; Bonini and Gandini) which do not even follow traditional musical genres but are often keyed to events and moods (Eriksson et al.; Hagen; Siles et al., "Genres"), as exemplified by Nostalgic Jams, Bad Day, or Birthday. This has implications for how people experience music. On the one hand, Avdeeff suggests the decline of musical genres as categories of personal identity (e.g. a metalhead or a punk) contributes to more eclecticism. On the other hand, Siles and colleagues ("Genres") argue that playlists have merely ushered in a new vocabulary—that “affective genres” have become the new grammar for musical identity organisation.
Like the mixtape, the playlist can be a highly personal creation, and complements the tendency found in listeners to use music as an archival practice, saving it to remember life events (Hagen; Lüders)—a practice that Lüders notes sometimes puts them at odds with streaming platforms’ incentive to push new “discoveries”. Yet the playlist is also personalised. As part of what’s been called the “algorithmic-streaming phase” (Maasø and Spilker 4), Spotify now generates a range of playlists, many of which have little human contribution (Hagen; Dias et al.). Although listeners can still create their own playlists, Spotify also offers entirely algorithmically created playlists, such as Discover Weekly and Daily Mix, which are personalised for each user based on tastes and listening habits (Types of Spotify Playlists).
In addition to the purely algorithmically created playlists, Spotify also involves human editors in the creation of playlists. “Editorial playlists” are created by Spotify staff based on “data-informed” choices (“Made by Editors”). These are organised around themes such as Rock, K-Pop, Workout, Trending, Gaming, Netflix, and—important to this study—Holiday, and are also tailored to domestic artists, national holidays, and even upcoming local concerts (Belanger). Editorial playlists are further personalised through what Spotify calls an “algotorial” process, in which the initial pool of human-chosen songs is filled in with songs personalised to each user’s taste (Barthle; Bonini and Gandini).
Hodgson notes that an irony of Spotify’s personalisation is that, even as the platform seeks to recreate the human touch of music recommendations, these “personalised” recommendations for every user are by necessity machine-generated, due to the scale of the platform (8). The push toward machine-generated playlists has been credited with creating new incentives in the music industry, as we will discuss in the next section.
Streaming Services and Linguistic Diversity
Spotify’s role in shaping listeners’ discovery of new tracks and artists, and the necessity to do this at scale, has raised concerns about how the platform is influencing both music listening and musical creation. Rather than democratising music, scholars have argued that Spotify pushes artists toward certain types of sounds because they maximise user engagement and playlist inclusion (Hodgson; Siles et al., "Playing").
While platforms often claim cosmopolitan intermingling in their marketing (Elkins), for smaller countries especially streaming platforms present potential threats to the national music industry and may further exacerbate the Americanisation of popular culture (Achterberg et al.; Verboord and Branderello; van der Hoeven et al.). As a Norwegian government report warned, “international streaming services pose a particular challenge to Norwegian music, because Norwegian listeners listen less to Norwegian music and more to foreign music through these global services” (Eidsvold-Tøien et al. 12). Language dominance can be further reinforced when artists from non-Anglophone countries choose to sing in English rather than their native tongue, in order to gain access to a wider global audience (Verboord and Branderello; van der Hoeven et al.).
Even so, empirical findings have been mixed. Demont-Heinrich found that English-language songs dominate global streaming charts, with Spanish-language songs following at a distance. Likewise, Aguiar and Waldfogel find that American music still dominates global lists, though domestic music accounted for about one out of five songs on New Music Friday playlists (688). Contrastingly, an analysis by Bello and Garcia found increasing diversity over time on Spotify and iTunes' most-streamed lists. Moreover, they find growing taste divergence between countries, mirroring Page and Dalla Riva’s finding of glocalisation in European music charts, where chart-topping songs are increasingly domestic. Research from the listener perspective suggests that the reasons audiences have for selecting music in their own language or in English are complex. Certain genres are rooted in local identities, while others are identified with cosmopolitan values and legitimised by being in English; meanwhile, diverse socioeconomic factors can influence the choice of cultural products (Meuleman and Savage; van der Hoeven et al).
Yet despite the central role of playlists in listening habits, and the increasingly central role of algorithms in creating them, little research so far has investigated the differences between human- and platform-created playlists—particularly with an eye toward language. We take up this question by exploring language diversity in music listening in Norway, focussing on the genre of Christmas.
Christmas Music
As December approaches, pop music slows down and Christmas music takes over. It is a moment of musical nostalgia, when we “look forward to looking back” (Arbide 96)—so much so that researchers have noted seasonal shifts in Spotify listening patterns in Christian-dominant countries (Bello and Garcia; Mok et al.). This genre, deeply rooted in Victorian England's Industrial Revolution, initially served to promote middle-class family values and moral conduct among the working population (Whiteley). Christmas music focussed on themes of benevolence, charity, and the importance of family. With the arrival of recorded music, radio, and television, Christmas music became a pop subgenre, largely through recordings of Victorian-era “classics”. Today, as more users choose to stream Christmas music in December, it has also become an important economic event for musicians (Maasø).
Yet even within the fairly narrow—even cloyingly homogenous—genre that is Christmas music, it is also characterised by music that subverts the genre (Whiteley; Jarman-Ivens). From Elvis’s conversion of Christmas songs into love songs—seen as profane by some U.S. radio stations (Whiteley 101)—to the loneliness and social critique in Joni Mitchell’s River and The Pogues’ Fairytale of New York, artists have challenged the unproblematically joyful nostalgia of Christmas music (Whiteley; Jarman-Ivens).
Christmas traditions in Nordic countries, though heavily influenced by commercialised Anglophone customs, historically possess a darker undertone (Bjerkeland), and are more deeply intertwined with national identity and community in these otherwise secular countries (Hebert et al.; Lundmark). Many Nordic artists record Christmas songs in their national languages that resonate with regional audiences and reflect the cultural significance of winter “coziness”, a concept popularised internationally by Denmark’s hygge. Many of these songs also reflect what Schiermer and Carlsen describe as an ambivalent attitude toward the profit-driven traditions now prevalent during the holiday period in the Nordics (169).
We thus consider Christmas music to be a culturally rich, yet specific enough genre that will allow for comparison between user and Spotify playlists. In the next section, we describe our data and analytical approach.
Method
Our methodological approach uses what we have called reciprocal digital methods, which place digital trace data in the context of users’ self-described digital practices (Robinson and Cole). Interviews with Spotify users were conducted in 2022 and 2023 as part of a project on music streaming and algorithmic knowledge (Cole). Spotify Premium users over 18 were recruited through snowball sampling starting at libraries, record stores, university campuses, and through acquaintances. From a larger international sample of 20, nine Norwegian participants aged 25–51 (M = 36; six female) were selected for this study. In addition to being interviewed, these participants have also donated their Spotify data, which include their streaming history and self-created playlists. Of the nine Norwegian participants, seven had created one or more Christmas playlists; one playlist did not have any data, so has been excluded.
Mirroring the number of participant playlists, Spotify’s top six playlists in the Popular Holiday Playlists section of Spotify’s Happy Holidays genre were accessed through the Spotify API (see tab. 1). To avoid personalisation based on listening history, the API was accessed via a new account; this account was created from a Norwegian IP address, the age given was 36 (the participant average), and no gender was given (“Rather not say”).

The user- and Spotify-created playlists were mapped in the program Gephi, with shared artists connecting playlists. In addition to visual analysis, we consider average degree and modularity of the networks. Average degree shows how many times an artist appears on different playlists. Modularity (Blondel et al.) calculates the number of communities, as well as the overall tendency of the network to group into communities.
To assess linguistic diversity, the language of each song was labelled, based on the title and artist, in ChatGPT, and then manually reviewed by the authors. We then calculate Shannon’s Diversity Index for each playlist and average this for each group of playlists. This index, often applied in ecology and linguistics, considers not only richness (the total count of different languages) but also evenness (how the total number of songs is distributed among those languages) while accounting for the relative size of each playlist.
The Personal vs. the Personalised
In interviews with participants, we learned that playlist creation was an important mode of organising their musical taste. As in previous studies, participants described using playlists for archival purposes—associated with certain events—as well as for organising their tastes into genres, moods, and specific artists, or even language. Participant 9 (M, 41yo) compared his approach to the pre-Spotify novel High Fidelity, in which the protagonist considers making mix tapes an art form. “I would never play shuffle”, Participant 9 said, “I want to decide what I [listen to]”, highlighting the importance of the human touch. He said Spotify makes it harder to find something that feels “rare” because “everyone has access to everything. So, you aren’t special. You’re just one more”.
Some participants enjoyed using Spotify’s playlists when they were tired of their own playlists or were looking to discover and explore new music. However, while participants liked how personalised Spotify playlists can be, these playlists feel artificial and monotonous. As Participant 13 (F, 27yo) explained: “sometimes they put too many songs that I already know and sometimes maybe I would want something different. ... They have the same songs, in every playlist, almost. ... It can be repetitive and boring”. In the interviews, several participants said they enjoy listening to music in a variety of languages and genres, which Spotify often fails to recommend.
While participants were not asked about Christmas music specifically, they did describe tailoring their music to particular seasons and occasions. Music was a way to revisit moments in life. “I know that there are periods in there so I can kind of go back and say, ok, now I want to listen to this period”, said Participant 7 (M, 32yo). This convergence between memory and music has been described in the literature on Christmas music, and indeed, the majority of the Norwegian participants did have Christmas playlists. We next take a quantitative approach to exploring these playlists further, and analyse how they compare with Spotify-created playlists.
Christmas Playlists
In order to establish the connections between playlists, we created networks based on the artists that appear in each playlist. Fig. 1 shows these visualisations, in which playlists are drawn together (or repelled from each other) by their mutual inclusion of artists (or lack thereof). Key artists, based on their shared appearance on playlists in the network, are labelled. (We used artists rather than songs because many Christmas recordings share the same name.)

Fig. 1: Artist Networks A, B, & C.
In fig. 1a, we see that the participants share American classics from Nat King Cole and Frank Sinatra, as well as songs from Norwegian artists Bugge Wesseltoft and Nils Bech. Comparing this to fig. 1b, we see the Spotify-created playlists share more artists in common. The Spotify network has a few clusters of playlists (denoted by the colourisation), while in the participant network playlists tend to be their own islands. Participant 7’s Jól playlist is entirely disconnected, suggesting that some users interpret even a narrow genre like Christmas very differently. The differences in shared artists are also notable. While all playlists can be considered part of the Christmas pop subgenre, contemporary pop artists singing conventional Christmas songs, such as Michael Bublé and Ariana Grande, as well as perennial favourite Mariah Carey, are key connectors in the Spotify network. Meanwhile, in the participant network, Joni Mitchell, Elvis, and John Lennon are important links between clusters.
In fig. 1c, we have combined the networks. The artists that appear on both Spotify and participant playlists have been labelled. Given that the participants are Norwegian, and several of the Spotify playlists are global, we expected Spotify’s Norwegian playlists (Julen er her, Norske Julesanger, Nye julelåter, Juleparty 2023) to be most connected to the Norwegian participants. This is not the case. Spotify playlists continue to constitute their own communities, and if anything, the participants’ playlists are more connected to the global playlists (Christmas Classics, Christmas Hits). In fact, the previously disconnected playlist (Jól) is now connected, thanks to the appearance of José Feliciano’s Feliz Navidad on Spotify’s Christmas Classics.
The Language of Christmas
Fig. 2 shows the same networks of playlists from fig. 1, but this time the playlists have been linked to language nodes based on the language of each song. We see that Spotify playlists are largely divided between English and Norwegian, and the communities from fig. 1b generally map onto the communities created by language in fig. 2b, though Julen er her now clusters with the Christmas Classics and Christmas Hits. The participant networks, on the other hand, not only have songs in more languages but are not as defined by language as the Spotify network. Moving from fig. 1a to 2a, we see that playlists are not clustered in the same communities. Even the two playlists by Participant 5 (Jul and Julelunsj) do not group together—though we see Jól by Participant 7 may constitute its own cluster due to its remarkable linguistic eclecticism. We confirm the respective diversity of languages mathematically using Shannon’s Diversity Index.

Fig. 2: Language Networks A and B.
Fig. 2 highlights another distinction: the Spotify playlists overall feature more Norwegian than the user playlists. This is visible in the thickness of the lines in fig. 2, but we also confirm this with a one-sided t-test. The participants’ playlists average 15% Norwegian, while Spotify playlists average 51% Norwegian, t(5.9)=2.01, p=.05, equal variances not assumed. This is a remarkable difference considering the calculation includes Spotify’s English-only global playlists.
In other words, despite more reuse of the same artists and the overall lower linguistic diversity in Spotify playlists, the platform-created playlists feature a higher proportion of Norwegian music than the participant-created playlists do.
Conclusion: Real or Artificial?
In analysing the networks created from user- and Spotify-curated Christmas playlists, distinct patterns emerge that complicate previous discourses on both the eclectic potential of streaming platforms and their influence on musical diversity (Prey; Hagen; Siles et al., "Genres"). The results are of course limited by a small, non-random sample of users, and a highly specific music genre. Even so, the study provides an entry point into exploring the differences between user- and platform-created playlists. Overall, users demonstrate a desire for personalised and diverse musical experiences, both in interviews and in their playlist compositions. Meanwhile, Spotify’s algorithms—designed to cater to broad user bases—sometimes prioritise uniformity and familiarity. Yet, in doing so, they promote the national language.      
As hinted at in the interviews, user-generated playlists exhibit a greater degree of linguistic diversity compared to those curated by Spotify. The playlist data show the participants to be effectively taste islands, tending to incorporate a broader range of languages and songs within their playlists—even within the narrow genre of Christmas music. These playlists also include more songs that challenge the “dominant Christmas values” (Jarman-Ivens 131), and even non-Christmas songs, indicating a level of personal expression and exploration that is not as prevalent in the “artificial”, platform-generated playlists. Spotify-curated playlists show a tendency towards linguistic segregation, featuring nearly all-Norwegian or all-English playlists, and with a narrower range of languages represented overall. The playlists also tend to be more similar to each other—even those created by human editors at Spotify—, suggesting a more standardised approach to playlist creation. This could be attributed to both the human and the algorithms’ reliance on popularity metrics and user listening habits. Yet by promoting playlists that emphasise Norwegian songs, Spotify potentially contributes to the reinforcement and revitalisation of national cultural expressions during the holiday season.
One way of seeing these results is that Spotify and user-created playlists serve different purposes. For example, users’ playlists may show more eclecticism precisely because they know that Spotify’s playlists have the old familiar standards—their playlists being reactively shaped by the platform. Harder to piece apart is the way that users’ tastes are likely directly shaped by Spotify recommendations (Seaver). In other words, as we grapple with what constitutes authenticity in digital spaces, the difference between the real and the artificial—between personal taste and algorithmic influence—may be less of a dichotomy than a constant interplay.
Acknowledgments
The authors would like to thank Áine Mangaoang at the University of Oslo's Department of Musicology and Arnt Maasø at the University of Oslo's Department of Media and Communication for their help with this article.
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