Music Creators on Douyin: 37 Indexed

This is the pool of Music creators on Douyin within Entertainment — 37 of them. The narrower the niche, the higher the reply rate; searching broadly for "Entertainment creators" usually spends budget on audiences that do not overlap yours.

How this slice differs from the index as a whole

• Median following is 336,252, 84.5× the index-wide median of 3,981 — expect higher rate cards.
• A and B grades are 5% of this slice versus 37% overall — expect to screen through more names to find usable ones.
• 68% have recent content captured for judgement versus 45% overall — better-evidenced than average.

How to read these numbers: this covers creators indexed and validated inside Koinon Link, not every creator on the platform. Suspected bought-follower accounts are quarantined and excluded from the table above (shown separately). The authenticity score is our own anomaly detection over follower/engagement structure, not a platform-official metric. Figures update as collection continues.

Creators in this slice

• 阿悠悠7.25号 北京站 (@58862693224) — Original songs like 'Old Dream Once'

• 震震有词 (@103161042836) — singing covers

• 永哥爱剪辑 (@75639934032) — Classic old song retrospectives

• 陈卓璇（8.29杭州站巡演版） (@77190587722) — 2026 Dangshi Tour presale and ticket launch

• 米拓果果 （女中音 词曲原创） (@1657709867305383) — Original song creation

• 张叶蕾Leafy（0926宁波巡演生日场 (@94137698414) — Tours and live performances

• 低音赵鹏 (@95011233917) — Classic old song covers and bass renditions

• 铃声大全APP (@lingshengdaquan) — TikTok trending songs

• 爱音乐APP (@917285746) — Douyin trending song recommendations

• River弹吉他 (@Tiktok_Chinyu) — Guitar practice for children

Ordered by follower tier, first 10 shown. Each link opens that creator’s public profile: what they post about, who reads it, and recent samples — no contact details.

Top 6 countries

Why this niche deserves its own view

"Music" is defined by who the audience is and what job they do, not by what the creator posts about. Two creators can both cover AI tools while their audiences barely overlap — one talks to media buyers who care about creative and bids, the other to engineers who care about APIs and deployment. Searching by topic mixes them together; searching by audience function does not.