66

Channel
武汉顶美点评
@NBN8899
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
5,886subscribers
-90 since we began measuring on 12 August 2026
Risers and fallers across the register · movement among entries of 3,162–10,000.
Register entry
| Telegram ID | -1004407400141 |
|---|---|
| Type | Channel |
| Username | @NBN8899 |
| Created | Between 1 June 2026 and 12 August 2026 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 12 August 2026 |
| Last confirmed live | 11 November 2026 |
| Measurements held | 23 |
| Confirmed unchanged | 1 time, most recently 11 November 2026 |
| On Telegram | t.me/NBN8899 |
Topic
Other / unclassifiable — 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 12 September 2026 and assigned it the closest of 31 fixed categories, at 56% 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 the other topics.
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 11 Nov 2026, 16:20 | 5,886 | -29 |
| 7 Nov 2026, 20:56 | 5,915 | -27 |
| 4 Nov 2026, 13:49 | 5,942 | -13 |
| 1 Nov 2026, 22:06 | 5,955 | -46 |
| 29 Oct 2026, 12:18 | 6,001 | -44 |
| 26 Oct 2026, 02:58 | 6,045 | -29 |
| 22 Oct 2026, 22:56 | 6,074 | -17 |
| 20 Oct 2026, 01:59 | 6,091 | -8 |
| 17 Oct 2026, 08:00 | 6,099 | -10 |
| 11 Oct 2026, 12:41 | 6,109 | +31 |
| 5 Oct 2026, 10:17 | 6,078 | -50 |
| 27 Sept 2026, 15:39 | 6,128 | -80 |
| 16 Sept 2026, 01:20 | 6,208 | -31 |
| 11 Sept 2026, 22:42 | 6,239 | +8 |
| 7 Sept 2026, 09:35 | 6,231 | -6 |
| 2 Sept 2026, 06:16 | 6,237 | -3 |
| 29 Aug 2026, 22:36 | 6,240 | -13 |
| 27 Aug 2026, 02:14 | 6,253 | +41 |
| 24 Aug 2026, 00:42 | 6,212 | +74 |
| 20 Aug 2026, 00:06 | 6,138 | first reading |
Engagement
30 posts held, back to 12 August 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 3 pages of Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 10.7%
- avg views ÷ 5,886 subscribers
- Avg views / post
- 632
- 18 posts measured
- Reaction rate
- 0.071%
- reactions ÷ views · ER floor
- Posts in window
- 18
- of 30 held
ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.
ER is defined industry-wide as (forwards + reactions + comments) ÷ views — note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate. It is computed over the 5 of 18 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 3 November 2026 |
|---|---|
| Posts held | 30 (12 August 2026 – 3 November 2026) |
| Views total | 11,374 |
| Reactions total | 2 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 5 Nov 2026, 01:09 UTC |
Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.
Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.
Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.
What this channel posts
- Video runtime
- 19s
- Average length
- 19s
Measured directly from 1 video with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.
Reaction mix
2 reactions across 2 posts, in 1 kind.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 2 | 100.0% |
No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.
Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.
Coverage. Reactions were read on 5 of the 30 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 2 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 30 most recent posts we hold, published 12 August 2026 to 3 November 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
Recent posts
Telegram’s own ‘edited’ marker: 0 of 18 posts held from the last 30 days (0%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).
Photo, posted without a caption
Photo, posted without a caption
❤1
Photo, posted without a caption
《暗香浮动·褪甲之夜》 跟着前台,在幽暗的灯光下,我走进了房间,空气里浮动着微温的精油与檀香。室内的光线昏暗,只有几盏暧昧红色的壁灯在按摩床上投下柔和的光晕!趴在按摩床上,空气里夹杂动听的音乐声,技师88号推开门,向我轻声问好!看那绝美白嫩的身体,我心动了,也兴奋了起来! 随后我进去浴室,温热的水流从花洒中倾泻而下,冲刷着积聚了身体的疲惫与尘埃。擦干身体后,房间里混合着技师的体香,柔和的光线拉长了两人的影子。她的双手带着适宜的温度,从后颈开始向下延伸。双肘与掌根精准地碾过僵硬的脊柱两侧,力道由轻到重,每一次揉捏都将深层的酸痛一点点剥离。随着身体的彻底放松,皮肤对温度与触碰的敏感度被无限放大。顺着腰窝一路向下,指尖在敏感的肌肤上轻柔而缓慢地划过——那是极具挑逗性的指滑,带起一阵阵酥麻的战栗。伴随着指尖的游走,温热的唇印随之落下,从耳后、颈侧一路向下蜿蜒,滚烫的呼吸喷洒在敏感的肌肤上,激起密密麻麻的颤抖。唇舌的辗转与细腻的指尖交织,…
66身材比图片还惊艳 服务很配合很有耐心 下次还来
88号,高颜值,服务无敌,大长腿,极品身材,夯爆啦
88号
66号服务好 身材超级棒 很喜欢 下次还来找她🌷🌷
66号服务很好 很耐心 身材也是相当哇塞😍😍😍
Photo, posted without a caption
66号身材很好啊 手感好 很年轻 喜欢
Showing the 12 most recent of 30 posts we hold for @NBN8899. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Mentions
Named by 13 registered channels — 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.
Named by
Channels on the register whose posts name this channel's handle.
@wuhangeren69 · 36,86710 posts武汉出击资源
@jljri · 72,2177 posts武汉认证榜
@LG88995 · 37,4715 posts武汉认证资源
@cph996 · 33,7143 posts🅥 武汉老师榜 🅥
@wuhanhua1 · 110,1932 posts厦门桃花阁公开榜
@fengxiangbao · 5,0941 post武汉八戒技师自拍馆
@NBB8887 · 1,7411 post武汉骑士榜(突击版)
@WHDTHYXCBB · 26,9841 post武汉会所榜
@WHJEHDB6 · 1,1081 post🅥武汉老师车评🅥
@whlou4 · 42,9651 post武汉楼凤榜 🅥
@wuhanbc · 109,5051 post🅥武汉老师报告🅥
@wuhanhua2 · 17,6371 post武汉第三深情
@wulixuxue · 15,9471 post
Names
Channels on the register whose handles appear in this channel's posts.
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 11 November 2026 — this entry's latest reading, not the date you are reading this.
“武汉顶美点评” (@NBN8899), 5,886 subscribers as measured 11 November 2026. Telegram Register, tgregister.com/channel/NBN8899.
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.