Ella Langley’s “Choosin’ Texas” logged 24 weeks atop the chart, passing the 22-week record held by Mariah Carey’s “All I Want for Christmas Is You,” the Christmas staple you can’t escape hearing every winter. The run finally ended on the chart dated Oct. 10, when Taylor Swift’s “Patient Zero” debuted at No. 1. Carey’s song, which tends to return to No. 1 each December, would need three more weeks at the top to reclaim the record.

Just 24% of U.S. music listeners knew of Ella Langley in the second quarter of 2026, according to entertainment data and research company Luminate, which shared the figures with Fortune. That was up from 13% in the fourth quarter of 2025 and 17% in the first quarter of this year. Her recognition was growing, but it still reached fewer than one in four music listeners.

A No. 1 hit, apparently, can still leave people asking, “Who?” So what happened to monoculture?

For those unfamiliar with the term, monoculture is a shared set of cultural references: the songs, shows, and movies you could assume other people knew, whether they liked them or not. (Lately, the word has also taken on a second, almost opposite meaning, as critics use it to describe how algorithms and AI flatten culture into sameness.)

It was easier to share references when so much of what people watched and heard came through a few television networks, radio stations, and MTV. Industry gatekeepers picked what reached a mass audience. You didn’t have to be a fan to know what everyone was talking about.

That shared audience was never everyone, and it began fragmenting before TikTok. But personalized feeds take the division further: What reaches you increasingly depends on what the system thinks you, specifically, will want to see.

Take TikTok, which touts the personalization of its For You feed. As the company explains, “there’s no one For You feed.”

Has this ever happened to you? You open social media, watch one Olivia Rodrigo concert clip, and suddenly it feels like every fifth video is another one.

TikTok says it takes cues from what you like and share, who you follow, and whether you watch a video to the end. It also looks at the videos themselves: their captions, sounds, and hashtags. Even your language preference, country setting, and device type factor in, though TikTok says those carry less weight. All of that helps the system decide what deserves another few seconds of your attention. TikTok says it also works to keep feeds varied, for example by generally not showing two videos in a row that use the same sound or come from the same creator.

In the U.S., that system is now overseen by the Oracle-backed joint venture that took over TikTok’s American operations in January, which has said it will retrain the recommendation algorithm on U.S. user data.

The feedback loop in action

Keep watching, and the algorithm may keep serving up more of the same. Researchers have observed that feedback loop in action.

A study published in EPJ Data Science in February tested TikTok’s For You feed using automated accounts programmed with different interests. It found that TikTok increasingly recommended videos matching those interests, with that reinforcement typically kicking in within the first 200 videos watched. The feeds kept some variety, but the more strongly an account’s interests were amplified, the fewer different hashtags it tended to encounter. (The researchers ran their experiments in 2024, before TikTok’s U.S. ownership change.)

That helps explain why you think something is taking over the internet, while Joe next door gets a completely different feed and wonders what you’re talking about.

You can also help narrow the selection yourself. Platforms like TikTok offer tools, such as its “Manage Topics” setting, that let you tell the system which topics you want to see more or less of.

Watching from all sides

The clues used to personalize your feed can even come from outside the app.

Meta announced in June that it would use information other businesses already share with it, like purchases people make on other websites, to personalize users’ feeds and AI responses, not just ads. The company’s own example: Buy a tent online, and you might start seeing more camping Reels. Users can manage this through a setting called “Activity from other businesses.”

What you watch, what you buy—it can all feed into the calculation, shaping your own little corner of the internet. One just for you.

Not everyone is a fan. New Yorker writer Kyle Chayka has a few complaints about that convenience—a whole book’s worth, in fact: “Filterworld: How Algorithms Flattened Culture.”

“These digital platforms and feeds, they kind of promise a great communal experience … but I think they’re actually kind of atomizing our experiences, because we can never tell what other people are seeing in their own feeds,” he told NPR’s Fresh Air in 2024.

That, he argued, takes some of the joy out of art and makes it harder for people to get excited about the same things.

Smarter algorithms may leave us in separate bubbles. But if something doesn’t interest you, do you really want it in your feed just for a shared cultural experience? And if it never reaches you, how would you know whether you’d like it?