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TikTok vs. Spotify: Research Reveals Two Distinct Music Ecosystems
In A Nutshell
- Most songs in the study charted on Spotify before showing up on TikTok’s Top 100, suggesting Spotify often leads the discovery curve.
- TikTok’s charts are far more concentrated than Spotify’s, with only 321 unique hit songs over two years compared to 1,707 on Spotify.
- Independent artists hold a notably larger share of TikTok’s charts than Spotify’s, where major labels dominate at roughly 76%.
- What a song is about matters on Spotify: love songs perform better, politically themed songs perform worse, but lyrical content shows no meaningful link to TikTok chart success.
Conventional wisdom says TikTok is where songs go to blow up. A short clip goes viral, a dance challenge spreads, and suddenly an unknown artist is topping the charts. A new two-year study of daily hit song data on both TikTok and Spotify finds that story is only partly true, and in at least one key way, the research flips the script signficantly.
Many songs in the dataset charted on Spotify before they ever appeared in TikTok’s Top 100. Independent artists, meanwhile, appear to have a fairer shot on TikTok than on platforms like Spotify. And the two platforms are governed by such different rules that they can feel like parallel music ecosystems, even as they remain connected.
Researchers at Renmin University of China, the Chinese University of Hong Kong, Tsinghua University, and the University of California, Davis, analyzed daily Top-100 hit song charts from both platforms spanning June 2020 through May 2022. Their findings, published in the journal Information, Communication & Society, draw on more than 2,000 unique songs and amount to one of the first hard-data comparisons of how TikTok and Spotify each shape what music people hear.
TikTok vs. Spotify: The Hit Song Pool Gap Is Enormous
Over the full two-year study period, only 321 distinct songs appeared on TikTok’s daily Top-100 chart. Spotify’s chart, over the same stretch, featured 1,707 unique songs. TikTok’s chart is dominated by a small, slow-rotating cast of tracks that linger far longer than anything on Spotify.
The authors suggest this may reflect TikTok’s algorithm doing exactly what it is designed to do. When a sound catches fire on TikTok, the platform’s recommendation engine pushes it to more users, more creators attach it to their videos, dance challenges multiply through hashtags, and the cycle keeps the song locked in place. TikTok’s video editing interface even nudges creators toward already-popular soundtracks, pushing those songs in front of even more eyes. Getting onto TikTok’s Top 100 is hard, but once a song lands there, it tends to stay.
Spotify works differently. Its recommendation system is built around individual listening habits across an enormous library, which means the chart turns over far more frequently. Hits rise and fall as different audiences cycle through different sounds.
Spotify’s Charts Still Belong to the Major Labels
On Spotify, about 76% of daily Top-100 hits came from major labels, meaning Sony, Universal, or Warner. On TikTok, that figure dropped to roughly 55%, with independent labels claiming a meaningfully larger share.
This reflects how each platform makes money. Spotify generates revenue through subscriptions and advertising, sharing that money with artists and labels. Major labels, armed with large promotional budgets and deep relationships with playlist curators, know how to work that system. A well-placed track on a high-traffic Spotify playlist can rack up enormous streaming numbers fast, and major labels have the resources to make that happen.
TikTok tends to reward engagement and virality more than industry connections. A bedroom producer with no label backing and a genuinely catchy sound has a realistic shot at reaching millions, and the numbers bear that out.
There is an added twist. Once other variables were accounted for, major-label songs were actually associated with shorter chart runs on both platforms. Independent tracks stuck around longer on average, possibly because major labels tend to concentrate their promotional firepower into a short window around a release, while independent music may build more gradually through organic sharing.
What the Lyrics and Genre Data Reveal About TikTok vs. Spotify Hits
On Spotify, what a song is about matters. Tracks about love and relationships were associated with stronger chart performance, while songs touching on politics, social issues, or violence tended to do worse. On TikTok, no lyrical theme showed a meaningful connection to chart success at all.
That gap likely reflects how the platforms are used. Spotify streams full songs, giving listeners time to connect with the words. TikTok serves up short clips where the hook carries the moment, not the verses.
Genre follows the same logic. Spotify’s charts lean heavily toward Pop and Hip-hop/Rap/Trap. TikTok’s charts show more variety, with R&B/Soul and Dance music claiming larger shares. Dance was the one genre positively linked to chart performance on TikTok, a clear reflection of the platform’s culture of choreography challenges and movement-based content.
Spotify Often Sees Hits First, Then TikTok Amplifies Them
Of all the songs in the dataset, only 68 appeared on both platforms’ Top-100 charts during the study window. Within that group, about 74% entered Spotify’s chart before they ever showed up on TikTok’s. Only eight songs followed the reverse path. The same held for exits: 82% of shared hits left Spotify before they left TikTok.
A deeper look at 30 songs with enough overlapping chart data found that for five tracks, a rise in TikTok popularity was actually followed by a decline on Spotify, offering limited additional support for the idea that Spotify’s chart moment often comes first.
One plausible explanation is how major labels launch new music. A coordinated Spotify playlist campaign builds early momentum before TikTok creators discover a track and start building videos around it. From there, TikTok’s algorithm can run with it.
For most songs in the dataset, TikTok and Spotify popularity moved independently of one another, and the two platforms are rivals with little incentive to share data or coordinate. The cross-platform effect the researchers found is real but limited.
Still, the pattern is consistent enough to complicate TikTok’s reputation as the music industry’s primary discovery engine. For independent artists, TikTok may still be the most level playing field out there. But for mainstream hits, the data suggests many pass through Spotify before gaining traction on TikTok.
Disclaimer: This article is based on a peer-reviewed study analyzing hit song chart data from TikTok and Spotify between June 2020 and May 2022. The findings reflect patterns observed within that specific dataset and time period. The cross-platform influence findings are described by the authors as limited and inconclusive, and should not be interpreted as definitive proof of a universal discovery pipeline between the two platforms.
Paper Notes
Limitations
The study covers only TikTok and Spotify, which represent distinct user demographics, cultural contexts, and national operating environments, making it difficult to isolate which specific platform characteristics drove the observed results. The data collection period coincided with the first two years of the COVID-19 pandemic, when stay-at-home orders likely altered music consumption and production in ways that may not reflect normal conditions. The cross-platform analysis was also constrained by a small sample of songs appearing on both platforms (68 songs), limiting the strength of those conclusions. The researchers acknowledge their findings on cross-platform influence are suggestive rather than definitive.
Funding and Disclosures
No potential conflict of interest was reported by the authors. The paper does not disclose external funding sources.
Publication Details
Ta, N., Jiao, F., Lin, C., & Shen, C. (2026). A computational analysis of the platformization of music: Comparing hit songs on TikTok and Spotify. Information, Communication & Society, 29(3), 1041–1059. DOI: 10.1080/1369118X.2025.2539297. Na Ta is an associate professor at the Research Center of Journalism and Social Development and the School of Journalism and Communication, Renmin University of China. Fang Jiao is a PhD candidate at the School of Journalism and Communication, Chinese University of Hong Kong. Cong Lin is a PhD candidate at the School of Journalism and Communication, Tsinghua University. Cuihua Shen is a professor in the Department of Communication, University of California, Davis.
