Adorno’s Critique in the Age of the “For You” Page

Theodor Adorno died in 1969, decades before the first recommendation algorithm was written. Yet reading his critique of the “Culture Industry” today, it feels less like mid-century philosophy and more like a user manual for the TikTok “For You” page. Recommendation engines on modern platforms do not just process raw user data — likes, views, watch time — to suggest content we might enjoy. They go a step further: they predict what we want before we consciously want it, assembling a feed that feels like a mirror of our innermost tastes but is really a model built from the aggregated behavior of millions of statistically similar users. Through Adorno’s lens, this is not proof of our individuality. It is the ultimate engine of “pseudo-individuality,” a system where the “For You” page makes every user feel like the center of their own unique universe while quietly sorting them into the pre-digested categories the algorithm needs to function. The Culture Industry, perfected: our conformity sold back to us as personal choice.

This essay explores that premise through a single case: HUNTR/X’s “Golden,” the animated K-pop blockbuster that became one of the 15 most-streamed songs released in 2025. “Golden” works as a focal point because its comment section contains, in miniature, every dynamic Adorno theorized — standardization, pseudo-individuation, passive consumption — while also hosting forms of critical discourse his theory said could not exist. Drawing on an NLP analysis of 84,816 YouTube comments across all 15 most-streamed songs, this piece shows how digital engagement has largely standardized the listener’s response rather than liberating it. At the same time, it argues that modern platforms enable what I call “collective decoding”: a distributed, democratic form of cultural critique that Adorno’s framework has no room for.

The Corpus: 84,816 Comments Across 15 Songs

The data comes from a straightforward source: the Top Tracks of 2025 Global playlist on Spotify, which ranks the 50 most-streamed songs released that year. I pulled the top 15 and scraped every available YouTube comment from their official music videos using youtube-comment-downloader, sorted by popularity. The result was a corpus of 84,816 comments spanning artists from Alex Warren and Taylor Swift to Bad Bunny, Jin, JENNIE, and sombr.¹

The artist mix matters. Five of the 15 tracks are Bad Bunny’s, which means the corpus is genuinely multilingual — roughly 29,000 comments in English, 12,500 in Spanish, and the rest scattered across Dutch, Portuguese, Indonesian, Korean, Tagalog, and a dozen other languages. About 15,000 comments were too short or emoji-heavy for reliable language detection at all.

Before doing anything with NLP, the first thing to check is the most basic feature of the dataset: how long are these comments?

The answer is: overwhelmingly short. The median comment is 18 characters. The mean word count is 7.7. Nearly half the corpus — about 50,000 comments — is under 25 characters: emoji reactions, single words (“fire,” “mid”), timestamps, brief exclamations. Another 17% are trivial by any metric — too short or formulaic to carry any analytical content. If Adorno is right that the culture industry produces passive consumption, YouTube comment sections are exhibit A.

This pattern holds across every song. “Golden,” “The Fate of Ophelia,” “Don’t Say You Love Me,” “Ordinary” — the histogram shape is identical. Different artists, different genres, different languages, different fanbases: the same behavioral signature. The structural uniformity of listener response is itself a data point that Adorno would have recognized immediately.

Looking for Critique in the Wrong Places

The first instinct was to look for critical commentary where you would expect to find it: in the longest comments or the most-engaged ones.

It did not work. The longest comments sorted by likes are dominated by catharsis and glamor — people admiring artists, sharing song lyrics, posting translations, writing motivational messages, copying religious texts, telling stories about deceased family members, and posting copypasta (the generic fan-spam that is its own subculture within artist communities). The most-liked and most-replied comments tell a similar story: heartwarming narratives about beating cancer, calls for connection across time zones — “Anyone here in September 2025?” — and the kind of ritualistic community-building that Adorno would have filed under the catharsis function of mass culture.

Building a Critique Detector

Finding critique through engagement metrics was a dead end. So I built an NLP pipeline grounded in Adorno’s own theoretical categories.

The approach is regex-based — pattern matching, not machine learning. Each comment is run through three stages: data ingestion (schema validation, deduplication, emoji-only flagging), preprocessing (unicode normalization, URL and mention removal, feature extraction), and rule-based classification (curated regex patterns matched against six Adorno-grounded critique labels, with negation suppression to reduce false positives).

A few design choices matter. The pipeline is multi-label — a single comment can carry multiple critique dimensions simultaneously. FORMAL_RESISTANCE is inverse-polarity: it represents counter-evidence to Adorno, moments where a commenter recognizes genuine artistic complexity. And the system preserves the commenter’s original voice — no lowercasing, no slang removal — so ALL-CAPS emphasis and vernacular idioms survive intact.

Each pattern carries a confidence score (0.0–1.0) calibrated to how precisely the language maps to its Adorno category. A comment matching “all songs sound the same” gets a higher confidence than one containing just the word “generic,” because the former is unambiguously about structural interchangeability while the latter could mean almost anything.

The pipeline processed all 84,816 comments. It found 269 with identifiable engagement with cultural production mechanisms. That is 0.32% of the corpus.

Standardization and the Algorithm That Predicts Desire

In “On Popular Music,” Adorno argues that the structure of popular music is “pre-given and pre-accepted, before the actual experience of the music starts” (Adorno, 1941, p. 17). Every element — verse, chorus, bridge — slots into a rigid template that makes individual songs interchangeable. The culture industry does not produce art; it produces variations on a formula.

The 15 most-streamed songs of 2025 bear this out. The NLP pipeline flagged 81 comments under the STANDARDIZATION label, averaging a confidence score of 0.64. The telling detail is not just that the word “generic” appears but that it appears across completely different artists and genres: on Alex Warren’s “Ordinary” — “this is literally a basic radio song, is so generic” (@surferboypizza12); on Taylor Swift’s “The Fate of Ophelia” — “a generic boring comment for a generic boring song from a generic boring artist” (@dominichern9446); and on Tate McRae’s “Sports car” — “It actually sounds like generic K pop from like 5 years ago” (@azraksash). Listeners are picking up on something systemic, not pointing fingers at one bad song.

These threads come together most clearly on “Golden.” @The_Null_Theory calls the whole thing out: “purposely generic mind rot songs for children to enjoy..not because they are actually good music.” The word that matters here is “purposely”: standardization framed as a deliberate strategy. @iam1hobbit takes it further: “too many kpop songs today are custom built for tiktok — with choruses that are simply chanted with some viral dance move but without singing.” This comment catches a feedback loop Adorno never anticipated: the song is not just distributed through the algorithm. It is designed for it, reverse-engineered from the platform’s requirements for virality.

Adorno’s concept hits differently applied to the delivery system. In “A Social Critique of Radio Music,” he warns that radio atomizes music, severing listeners from “the structural wholeness of the work” (Adorno, 1945, p. 211). Today’s algorithms do not just distribute standardized music; they standardize the whole context of listening. A song shows up as a fifteen-second TikTok snippet, a playlist transition, a background loop. But the TikTok algorithm does something qualitatively different from radio. Radio broadcast the same content to everyone. The “For You” page builds what feels like a personal experience by predicting what each user wants to hear before they know they want to hear it. It does not wait for a listener to seek out “Golden”; it anticipates probable interest and serves the song proactively. This is Adorno’s “pre-given and pre-accepted” pushed to its logical extreme: the algorithm has pre-given not just the song’s structure but the listener’s desire for it.

Pseudo-Individualization and the Illusion of the Unique Universe

Adorno defines pseudo-individualization as “endowing cultural mass production with the halo of free choice or open market on the basis of standardization itself” (Adorno, 1941, p. 25). The “For You” page runs this trick at industrial scale through a mechanism Adorno never foresaw: the algorithmic construction of the user as a type. You open TikTok and it feels like the center of your own universe — one where “Golden” appears not because it is the biggest song of the moment but because you, specifically, were meant to find it. The problem is that the algorithm cannot work through genuine individuality. It runs on clusters: standardized behavioral types defined by watch-time patterns, engagement metrics, and demographic proxies. The “uniqueness” of each feed is really a classification system sorting millions of users into a limited set of pre-built categories. Adorno’s pseudo-individualization, written in code.

The NLP pipeline flagged exactly one comment under PSEUDO_INDIVIDUALIZATION — @bailee7696 on Tate McRae’s “Sports car”: “literally are carbon copy of buttons,” at a confidence of 0.75. A phrase that could serve as a dictionary definition of the concept: surface novelty concealing structural sameness. That there is only one explicit hit is itself a finding. Pseudo-individualization, among Adorno’s six dimensions, is the most ideologically effective precisely because it is the hardest to articulate. The branding veneer is so naturalized that few listeners name it directly. They circle it instead.

Commenters on “Golden” get at this without the theoretical vocabulary. @ruskiwaffle1991 says it flat out: “Funny thing is, K-pop is one of the most corporate music genres out there.” @ZhonWeak goes deeper, noting that “what makes a song nice isn’t just the names on the song title, there are people not named in the title who are the very reason why the song is amazing, ie the songwriters (not the singers most of the time for commercial music) and the producers.” That comment catches both halves of pseudo-individualization: the artist puts forward a false image of creative authorship, and the listener buys a false image of individual artistry.

The pipeline also flagged 14 comments under COMMODIFICATION / MARKET LOGIC (average confidence 0.77), including @fonumanukeu-bv9ty on “Golden”: “it was probably just a money grab.” What these commenters are articulating, in raw form, is the core of Adorno’s argument: that the industry manufactures both the product and the demand for it.

The Passive Listener and the Echo Chamber

Adorno’s most provocative claim is not just that popular music is standardized but that it produces standardized listeners — whose response is “pre-determined by the mechanism of popular music itself” (Adorno, 1941, p. 26). Recognition replaces cognition. Comfort replaces challenge.

The comment sections make a strong case for this: of 84,816 comments analyzed, only 269 — a mere 0.32% — contained any identifiable engagement with cultural production mechanisms. The vast majority consist of exactly the pre-programmed responses Adorno would have predicted: “This slaps,” “Who’s here in 2026?,” “I’m not crying, you’re crying.” These are not evaluations of music. They are performances of consumption, ritualistic declarations of belonging that mirror the standardized product they accompany.

The pipeline flagged 7 comments under REGRESSIVE LISTENING (average confidence 0.70). The sample is small but the language is pointed: “its terrible, elevator music...” and “another ordinary overprocessed pile of garbage got a bunch of listens from the mass of braindead ordinaries” (@Dr_Darrow, on Alex Warren’s “Ordinary”).

YouTube’s sorting algorithm makes it worse, promoting the most generic reactions to the top while burying substantive critique under emojis and time-stamped affirmations. On “Golden,” @The_Null_Theory names the audience condition: “purposely generic mind rot songs for children to enjoy..not because they are actually good music.” This is regressive listening translated into YouTube vernacular: the accusation that audiences have been conditioned into passivity by the very infrastructure they think is setting them free.

What the Classifier Reveals

Stepping back from individual categories, the aggregate picture is worth looking at.

FORMAL RESISTANCE dominates the count at 166 hits — but this requires context. Its average confidence is the lowest of all labels at 0.48, barely above the classification threshold. Many of these are comments containing words like “underrated,” “timeless,” or “refreshing” — language that signals appreciation for perceived artistic quality but does not always constitute a rigorous counter-argument to the Culture Industry. The word “underrated” alone accounts for 57 of the 166 hits.

By contrast, COMMODIFICATION / MARKET LOGIC and PSEUDO_INDIVIDUALIZATION, while rare, score the highest average confidence — 0.77 and 0.75 respectively. When commenters articulate these critiques, they tend to do so with precision: “cash grab,” “corporate music genre,” “carbon copy.” The language is unambiguous.

The co-occurrence matrix tells another story: labels almost never appear together. Only four comments in the entire corpus carry more than one critique label. Standardization co-occurs once each with Commodification, Regressive Listening, and Formal Resistance. Every other pairing is zero. This could mean the regex rules are too mutually exclusive — or it could mean that YouTube commenters, when they do engage critically, tend to focus on one dimension at a time.

The Critical Labor Adorno Could Not Envision

The strongest counter-argument to Adorno is to challenge the totality of his theory. He believes these mechanisms — standardization, pseudo-individualization, and regressive listening — are so pervasive that genuine critical consciousness becomes virtually impossible for the mass listener. But the same data that confirms his critique also undermines this conclusion, in a form he never imagined: a distributed, collective process of cultural decoding happening in the comment sections themselves.

The 269 critique-bearing comments represent something Adorno’s framework cannot account for: ordinary listeners doing real intellectual work. When a user argues over a song’s merits, calls out its formulaic structure, or maps its production logic onto their own experience, they are not passively consuming. They are decoding. And because they are doing it in a public forum visible to thousands, these individual acts of critique add up to something bigger: a collective form of cultural analysis that works without institutional authority or Adorno’s “privileged vantage point.”

The comment section beneath “Golden” is the clearest example. @ivobaki3751 writes: “I know how things are behind curtains in kpop world and as they sing lovely like angels everything i know makes me more resistant to its influence. Kids went bzrk about them and im sure these ladies good persons and all but the industry that generated entire show is what it is. Ive seen same pattern repeat too many times.”

Without any evident exposure to Frankfurt School theory, this commenter identifies standardization (“same pattern repeat too many times”), pseudo-individualization and commodification (artists who “sing lovely like angels” while the apparatus runs behind a curtain), and a conscious resistance to the product’s emotional pull. This is not the regressed listener Adorno described.

@sandyg4646 pushes the analysis further into the visual side: “k pop is extremely formulaic in its approach despite the mixing of different styles. You said it yourself ‘more focus on choreography and stage presence’ what does that tell you?” Notice this commenter is not just spotting a formula but challenging another user with a question — peer-to-peer critique happening in real time.

Even @estuchedepeluche2212, on sombr’s “undressed,” reaches for literary theory: “Derivative, not quite original, familiar, comforting, but oh, so good. As Umberto Ecco said: ‘The cliches are talking and they are having a ball!’” This is someone who holds pleasure and critique in the same hand. Adorno’s clean binary between critical and regressed listening cannot contain that kind of response.

What makes this genuinely difficult for Adorno’s theory is that it is collective and public. He imagined the critical listener as a solitary figure, trained in serious music, able to perceive what the masses could not. A YouTube comment section is not a seminar room. But it is a space where users argue, cite outside references, and build on each other’s observations in real time. That is collective decoding: intellectual labor performed by the audience itself, using the same platforms that deliver the product to take the product apart.

Conclusion

None of this erases the force of Adorno’s diagnosis. The 0.32% is still 0.32%.

If the “For You” page really is the culture industry perfected — predicting desire, disguising conformity as choice, pre-giving the whole before the experience even begins — then its triumph is nearly total. Standardization dominates the critique categories, directly echoing Adorno’s central claim from 1941. Pseudo-individualization is the rarest label — and its rarity likely reflects how effectively it works as ideology, so naturalized that few listeners can name it. The comment sections themselves are products of the same algorithmic logic that Adorno’s Commodification label targets: the medium and the message converge.

But “nearly” is doing important work in that sentence. The critical voices beneath “Golden” show that mass audiences are not the undifferentiated, regressed consumers Adorno imagined. The algorithm has not managed to silence the 0.32%. And the platforms that deliver “Golden” as a fifteen-second TikTok loop are the same ones hosting the collective decoding that picks it apart.

That the culture industry might generate the conditions for its own critique is, in the end, maybe the most Adornian irony of all.