Spotify Wrapped, Unpacked – Vox
When Spotify Wrapped came out in 2017, it hit my group chats like the breaking news. A friend frantically sent me a screenshot showing they were in the top 1% of Frank Ocean listeners with a “CAN U BELIEVE THIS” message, followed by a deluge of texts from other friends, highlighting their distinctions in streaming. Soon after, people all over the internet were sharing their listening results. Instagram stories were filled with streaming stats that poked fun at simpler tastes or flexed artistic inclinations. (I admit, I also shared mine.)
Spotify originally released its first iteration of Wrapped in 2015 as âYear in Music,â a feature that allows users to look back on their last 365 days via the songs and artists they listened to the most. The tool included statistics such as the songs the listener played the most and the number of hours of music they listened to in total. Although popular, Year in Music didn’t go viral, until it was upgraded two years later to the customizable, jazzy graphic version that it is now.
Now, Spotify Wrapped has become an annual tradition, marking the change of seasons in much the same way beloved cultural must-haves like Starbucks Holiday Mugs or Mariah Carey mark the holidays. But as Spotify’s functionality grew in popularity, a growing discourse about algorithms, the use of which has become standard procedure on social media, and upon which Wrapped relies, has grown.
An algorithm takes a set of inputs and generates an output, much like a recipe turns ingredients into a cake. For Spotify, relying on algorithms means it uses its consumers’ data to drive music discovery through playlists. Open the Spotify homepage and you can find a number of curated playlists that provide user data collected from the app, from âBest Songs in USAâ which aggregates collective data, to “Discover Weekly”, which is based on personalized data. To create these playlists, Spotify tracks the music you listen to, organizes it into certain categories, measures tracks against other listeners, and uses that information to choose the music to show you.
Spotify’s algorithmic delivery was what initially set it apart from other music streaming platforms, often cited as a big factor in the app’s success despite how it relies on tracking data. App user Kiana McBride, 22, told me, âMy Discover Weekly is often on fire. Spotify has such good data analysis that it can tell what music I’m likely to enjoy.
While tracking music data doesn’t seem too obscure at first glance, the use of artificial intelligence has proven to be discriminatory. Reports have shown how artificial intelligence can be coded with bias and perpetuate racism. Combined with video technology or security software, algorithms have also played a vital role in strengthening surveillance capitalism. There have even been reports of how inaccurate and poorly marketed the functionality of the platform is. Yet Spotify Wrapped is going viral. Our collective attachment to this rundown reveals how algorithms have integrated into the way we see ourselves in the digital consumer culture: as brands to be refined.
According to P. David Marshall, a new professor of media and communications at Deakin University and a leading specialist in online identity, the concept of “double strategic characters” profoundly informs the way people approach what they share on the Internet. social networks. “Double strategic character [uses] the word back and forth, âhe told me. âDual as in two, and duel, which means you actually start playing in a space that includes algorithmic transformations. ”
Consumers increasingly understand that the way they use an app influences the type of content they see, creating a digital double consciousness, where “we realize we are a digital construct”, but we also realize that ” a digital construct is linked to who we are. – who we think we are, âMarshall said. Essentially, our online selves are always an extension of ourselves; it’s not not a version of the personality. At the same time, it’s a version that is inherently fabricated and performative.
And as is the nature of performance, those who are on stage are called upon to act incessantly. We strategically build a certain perception of ourselves through snippets which, with the help of Spotify Wrapped and other algorithms, become more and more refined. For example, sharing a roundup on social media can position a person in a particular niche: independent; punk; Rock. If the musical genres are even more obscure, then this person can move into very specific niches: folktronica; rap cloud; Japanese urban pop.
An app user, Alfonso Velasquez, 22, told me he liked watching other people’s results on Spotify because in comparison “it makes him feel more independent.” He speaks to a brand curating instinct for himself – an instinct derived from the culture of dominant influence.
âInfluencers are in this split-personality structure, working between a corporate version of themselves and a highly individualized version of themselves,â Marshall said. For this reason, they âchange our larger transnational culture as to what is normalâ.
Another user, Isabel Edreva, 21, told me that she looked at other people’s findings on Spotify to “take notes.”
“If someone I really respect has a song I’ve never heard of,” she explained, “I’m like ‘Okay, I should listen to it.'”
Many people don’t sign up taking Spotify Wrapped’s recommendations as influenced. But this is the crux of the culture of influence.
âWe’re starting to do variations of what influencers do,â Marshall said. âThey become our way of trying to understand life online and the way we begin, as ordinary people, to reconstruct our notion of a differentiated personality. When Internet celebrities such as singer Madison Beer, Musical.ly star and singer Loren Gray, or viral TikTok musician Laufey stream their results, the practice accelerates even further. Spotify Wrapped is just one example of how influencer habits, from what they post to how they post it, become a particular guide for everyone on the internet, no matter who you follow on them. social networks.
Spotify makes participating in this culture even easier. With a simple touch, the content – already produced in different coordinated colors – can be shared. Eye-catching graphics are pre-generated. Users can reveal a bit of themselves with low stakes and minimal participation, mindlessly mimicking how influencers exploit their tastes and interests to become a brand.
Perhaps it is this seamless participation with instant rewards for brand building that pales in comparison the mistrust of tracking your data on the platform. “These are just songs,” app user Sophronia Barone, 21, told me. “I guess that’s okay.”
Are these just songs, though? When analyzing the back-end of the application, a team of five researchers behind the 2019 study “Spotify Teardown: Inside the Black Box of Streaming Music” made it clear that algorithms do not exist. not in a vacuum. They wrote: âResearchers have demonstrated how the delivery of algorithmic content has implications for the production of gender, race and other categorizations. Users are encouraged – or forced – to transform their listening habits into âtaste profilesâ, which are measured using a set of parameters. “
Spotify hasn’t made these categories public, but academics have found that the genre is certainly one of them. They noted that Paul Lamere, director of music and data intelligence platform Echo Nest (which was acquired by Spotify in 2014), provided data based on listening habits by gender in an article by blog from 2014. Researchers have found that self-declaration of your gender is a mandatory part of the platform’s registration process and, moreover, is listed as one of the types of information that Spotify collects and shares within the framework of its confidentiality policy â, indicates[ing] this genre is seen as vital to the functioning of Spotify, at least for marketing purposes.
They also found out that the company knows your IP address – that is, your location, nationality, and by proxy, your social class. Another Bank of England study found that Spotify data can even reveal the mood of users. So it’s not unreasonable to assume that Spotify can infer a good chunk of your socio-economic demographics, reducing ethnicity, age, and maybe even sexuality if you listen to specific podcasts, like the popular one. from Spotify. Queerology. (And after a priest’s sexuality was recently exposed by a Catholic publication via his phone’s location data, it’s clear that this information has real consequences.) Spotify then capitalizes on that information by selling it to companies. , to which the demographic profiles are similar. gold.
Spotify, of course, isn’t the only company to be successful with their consumer marketing algorithms: everything from DigiScents, which promises to scent your home based on your web browsing history, to TikTok, the app. most popular social media platform around. , is about algorithm-based visualization and encourages us to buy a ridiculous amount of stuff. Discover the culture of AI, the new era of digital capitalism, where the consumer is constantly stuck in their own feedback loop. If you open an app, you are inherently giving businesses free work in the form of web traffic, AdSense, and taste profiles, only for those apps to sell your profile and user identity – which is essentially you. – to others, then finally, back to yourself. These companies are pushing us towards algorithmic visualization, and not only do we collect what their data reveals about us, but we also enthusiastically share it for others to see.
We do this in the name of self-branding. Because in the end, we get one more quantifiable piece to add to our ultra-specific online personality. For a fleeting moment, we can all be influencers too. âI love that Spotify is sharing their stats with you,â McBride said. It’s “like you’re an MLB star listening to music.”