Home & living Creators on X (Twitter): 25 Indexed

This is the pool of Home & living creators on X (Twitter) within Lifestyle — 25 of them. The narrower the niche, the higher the reply rate; searching broadly for "Lifestyle creators" usually spends budget on audiences that do not overlap yours.

How this slice differs from the index as a whole

• 100% have recent content captured for judgement versus 41% overall — better-evidenced than average.
• A and B grades are 16% of this slice versus 34% overall — expect to screen through more names to find usable ones.
• Median following is 2,963, 0.5× the index-wide median of 6,482 — a long tail of smaller creators: cheaper per deal, but more deals needed.

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

• การไฟฟ้านครหลวง MEA (@mea_news) — 电力诈骗防范

• Clintus🌵McGintus (@Clintus) — daily life documentation

• Fred Larucci 🎥🎬🇺🇸 (@NightGallery1) — Vintage stamp sales

• Apollo Hospitals, Chennai (@Apollo_Chennai) — Ergonomics and desk setup

• BIQU (@BIQU_Makers) — 3D printer hotend maintenance

• Bob Wiltse (@BobWiltse) — real estate listings

• City of Castle Pines (@CastlePines_Co) — Scam and fraud warnings

• India in Sierra Leone (@FreetownHci) — Indian handloom heritage

• 兵庫県警察安全安心情報 (@HPP_seiankikaku) — 特殊詐欺防止

• AnhHai (@HaiThanhNg) — 日常饮食

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

"Home & living" 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.