Channel
【日本福利专场】 ｜熟女｜乱伦｜剧情｜番号｜强奸
@fanhaotv
On this record: Topic · Growth · Engagement · Citations · Cite this entry
58,263subscribers
-400 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 31,623–100,000.
Register entry
| Telegram ID | -1002042733852 |
|---|---|
| Type | Channel |
| Username | @fanhaotv |
| Created | Between 1 November 2023 and 31 May 2024 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 11 August 2026 |
| Last confirmed live | 16 September 2026 |
| Measurements held | 32 |
| Confirmed unchanged | 1 time, most recently 16 September 2026 |
| On Telegram | t.me/fanhaotv |
Topic
Adult — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 9 September 2026 and assigned it the closest of 31 fixed categories, at 97% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and why it has no browse page of its own yet.
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 16 Sept 2026, 12:18 | 58,263 | -18 |
| 14 Sept 2026, 18:41 | 58,281 | +25 |
| 13 Sept 2026, 02:00 | 58,256 | -41 |
| 11 Sept 2026, 04:00 | 58,297 | -28 |
| 8 Sept 2026, 09:35 | 58,325 | -52 |
| 5 Sept 2026, 05:00 | 58,377 | -20 |
| 3 Sept 2026, 07:58 | 58,397 | -11 |
| 2 Sept 2026, 04:36 | 58,408 | -16 |
| 1 Sept 2026, 03:07 | 58,424 | +16 |
| 31 Aug 2026, 03:13 | 58,408 | -14 |
| 30 Aug 2026, 03:37 | 58,422 | -12 |
| 29 Aug 2026, 00:04 | 58,434 | -9 |
| 27 Aug 2026, 21:33 | 58,443 | +2 |
| 26 Aug 2026, 21:34 | 58,441 | -25 |
| 25 Aug 2026, 21:38 | 58,466 | -4 |
| 24 Aug 2026, 22:03 | 58,470 | -16 |
| 23 Aug 2026, 09:26 | 58,486 | -9 |
| 21 Aug 2026, 20:27 | 58,495 | -1 |
| 20 Aug 2026, 18:24 | 58,496 | +12 |
| 19 Aug 2026, 20:12 | 58,484 | first reading |
Engagement
No public post preview. We read this entry on 11 August 2026 and Telegram serves no public post stream for it — the channel has previews switched off, or it is a group or bot with no readable feed. Views, reactions and engagement rates cannot be measured from the outside for an entry in this state, so we publish none. Subscriber counts above are unaffected.
Mentions
Named by 1 registered channel — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.
A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.
Cite this entry
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 16 September 2026 — this entry's latest reading, not the date you are reading this.
“【日本福利专场】 ｜熟女｜乱伦｜剧情｜番号｜强奸” (@fanhaotv), 58,263 subscribers as measured 16 September 2026. Telegram Register, tgregister.com/channel/fanhaotv.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.