The Algorithmic Radicalization Of Culture SuperFans

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It is nighttime in Paris. We are more than a year into Taylor Swift’s Eras Tour, and tonight, her fans are once again trying to figure out what her clothes mean.

The star is in a glittering yellow-and-red two-piece set, a possible reference to the colors of the Kansas City Chiefs, the football team Swift’s boyfriend, Travis Kelce, plays on. This is also the 87th performance in the tour, and—aha!—Kelce wears jersey number 87. The hundreds of thousands of fans watching along through bootlegged livestreams on TikTok and YouTube have solved another mystery.

This is the beginning of the European leg of Eras, which will stretch on and on until Swift returns to North America this fall and plays the final show of the tour on December 8 (that is, assuming she doesn’t extend it, as she has multiple times already). You’d think people would have lost interest by now. But Taylor Swift has kept fans’ attention by tapping into an algorithmic machine unlike anyone has before her.

Swift is savvy, and leverages social-media culture to her advantage. Over her 18-year career, she has trained her fandom to inspect everything she does for Easter eggs; she knows that even a small reveal can send people into a frenzy. She likes to leave clues about upcoming music in her outfits, in music videos, even in commercials she films with brands. She knows people are interested in her personal life—her romances, her feuds—and capitalizes on that, leaving them hints in her liner notes or in song titles.

In response, fans analyze dates and look for numbers that add up to 13, her favorite number. They create spreadsheets of every single outfit she’s worn on tour, methodically tracking each surprise song she’s played. They chat nonstop across platforms, swapping elaborate theories to try to decode when the next album is coming or whom each song is about. For more than half a decade, they’ve been convinced that there’s a lost album called Karma, which was shelved in the mid-2010s amid Swift’s feud with Kanye West (now known as Ye) and Kim Kardashian. According to one theory, the orange outfits she’s been wearing in Paris are a sign that she’ll release music from Karma. It’s like QAnon, if QAnon involved a lot of DIY rhinestone boots.

Swifties don’t storm the Capitol, but they will flood Kardashian’s Instagram with snake emoji in response to Swift talking about the pain their fight brought her, just as they will fight Ticketmaster when the company botches her concert-ticket rollout. Their thinking is often conspiratorial. In one recent TikTok, a fan argued that Swift would be releasing something on May 3, according to this logic: A recent screenshot of a music-video still posted to Swift’s team’s Instagram included the letter-and-number combination 14.3V—Swift’s latest music video was for “Fortnight,” and a fortnight is two weeks; two weeks is 14 days. One plus four equals five. The three rounds it out: Something’s happening on the 3rd. The V is actually the Roman numeral for five. (May 3 came and went without a release.)

Extreme cliques might be one side effect of our digital culture. “Our algorithms and media are designed to produce fandoms around consumption goods,” Petter Törnberg, a professor of computational social science at the University of Amsterdam, told me over email. “There is hence a fundamental similarity between Swifties, Apple-fans and MAGA Republicans: our current era has the tendency of turning our preferences into identities, and shaping a form of postmodern tribes around both consumption goods and political leaders.” (See also: fans of Beyoncé and BTS.)

In other words: Social platforms can have a radicalizing effect on fandoms. When we study algorithmic radicalization, we tend to do so in the context of politics, but the same systems might also calcify our beliefs about cultural products. Yet we still have a fairly limited understanding of how all of this works. “The very best studies we have are still really struggling to detect effects, because there’s so many challenges when you try to study this stuff,” Chris Bail, the founding director of the Polarization Lab at Duke University, told me.

No one single algorithm powers this fandom. It operates across platforms; in a single day, a Swift fan might stream her music on Spotify, watch her music videos on YouTube, and consume posts about her on TikTok. All of these sites have distinct recommendation systems. Companies also tend to keep these systems a secret, making them hard to research.

But we can say this: Algorithms tend to reinforce what’s already popular, because attention attracts more attention. Growth begets growth, as Törnberg put it. In this way, Swift also demonstrates how platforms that supposedly target content based on an individual’s interests can, in fact, end up clustering around one monolithic force. “It just seems like, Oh, that’s sort of weird, I thought everybody was supposed to have their own algorithmic niche now,” Nick Seaver, the author of Computing Taste: Algorithms and the Makers of Music Recommendation, told me. “And instead—I mean, maybe in addition to that—we also all have Taylor Swift.

Our modern Swiftocracy is a reminder that we are still subject to strange algorithmic forces, even as the web is supposedly fractured. Yet the consequences of this can be as hard to decode as an Easter egg dropped by Swift. On her final show in Paris, she opted for a “berry”-red dress for the Folklore section of her set. It may be a sign of something to come. Or not.

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