💐老师:#青柠儿 😦#洪山 😦课费: 1000p 🐱电报: @Wh520055 ✏️频道: @Wh52005 🤖双向: @Qingning5210_bot 报告榜 报告模板 报告提交 聊天群1 : @wuhanp 聊天群2 : @wuhannn 楼凤榜 : @wuhanbc 上榜员 :@wuhanbbot

Channel
武汉楼凤榜 🅥
@wuhanbc
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Posts edited after publishing · Posts recorded as deleted · Citations · Handles named that no longer answer · Cite this entry
109,505subscribers
+34,838 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 100,000–316,228.
Register entry
| Telegram ID | -1002109293141 |
|---|---|
| Type | Channel |
| Username | @wuhanbc |
| Description | 榜单唯一管理员 / @wuhanbbot |
| Created | Between 1 November 2023 and 31 May 2024 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 12 November 2026 |
| Measurements held | 65 |
| Confirmed unchanged | 1 time, most recently 12 November 2026 |
| On Telegram | t.me/wuhanbc |
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 9 September 2026 and assigned it the closest of 31 fixed categories, at 83% 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 |
|---|---|---|
| 12 Nov 2026, 20:09 | 109,505 | +589 |
| 10 Nov 2026, 17:20 | 108,916 | +606 |
| 9 Nov 2026, 02:50 | 108,310 | -330 |
| 7 Nov 2026, 17:47 | 108,640 | -222 |
| 6 Nov 2026, 14:06 | 108,862 | +371 |
| 5 Nov 2026, 13:45 | 108,491 | +844 |
| 4 Nov 2026, 11:26 | 107,647 | +595 |
| 3 Nov 2026, 10:04 | 107,052 | +401 |
| 2 Nov 2026, 09:16 | 106,651 | +500 |
| 1 Nov 2026, 07:18 | 106,151 | +454 |
| 31 Oct 2026, 10:49 | 105,697 | +477 |
| 30 Oct 2026, 13:46 | 105,220 | -1,243 |
| 29 Oct 2026, 14:39 | 106,463 | +465 |
| 28 Oct 2026, 10:49 | 105,998 | +445 |
| 27 Oct 2026, 13:26 | 105,553 | +543 |
| 26 Oct 2026, 12:06 | 105,010 | +260 |
| 25 Oct 2026, 10:06 | 104,750 | +76 |
| 24 Oct 2026, 07:16 | 104,674 | +238 |
| 23 Oct 2026, 08:36 | 104,436 | +418 |
| 22 Oct 2026, 07:07 | 104,018 | first reading |
Engagement
970 posts held, back to 6 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 202 pages of Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 2.27%
- avg views ÷ 109,505 subscribers
- Avg views / post
- 2,480
- 361 posts measured
- Reaction rate
- 0.038%
- reactions ÷ views · ER floor
- Posts in window
- 362
- of 970 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 128 of 361 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 13 November 2026 |
|---|---|
| Posts held | 970 (6 August 2026 – 13 November 2026) |
| Views total | 896,199 |
| Reactions total | 129 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 13 Nov 2026, 22:05 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
- Photos
- ≈3,570
- Videos
- ≈562
- Links
- ≈1,140
Lifetime counters from Telegram’s own channel header, read 13 November 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.
- Video runtime
- 45m 52s
- Average length
- 10s
Measured directly from 287 videos 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
500 reactions across 366 posts, in 16 distinct kinds. The most used accounts for 82.4% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 412 | 82.4% | |
| 👍 | 31 | 6.20% | |
| 💩 | 10 | 2.00% | |
| 👀 | 9 | 1.80% | |
| 💯 | 9 | 1.80% | |
| 🎉 | 5 | 1.00% | |
| 👎 | 4 | 0.8% | |
| 🔥 | 4 | 0.8% | |
| 👏 | 3 | 0.6% | |
| 🤡 | 3 | 0.6% | |
| 😁 | 2 | 0.4% | |
| 😨 | 2 | 0.4% | |
| 🤣 | 2 | 0.4% | |
| 🤮 | 2 | 0.4% | |
| 👌 | 1 | 0.2% | |
| 🥱 | 1 | 0.2% |
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 429 of the 970 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 500 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 970 most recent posts we hold, published 6 August 2026 to 13 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: 42 of 362 posts held from the last 30 days (11.6%) 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).
💐老师:#小妲己 😦#汉阳 😦课费: 600p 1000pp 🐱电报: @daji0766 ✏️频道: @daji07666 🤖双向: @xiaodaji07666_bot 报告榜 报告模板 报告提交 聊天群1 : @wuhanp 聊天群2 : @wuhannn 楼凤榜 : @wuhanbc 上榜员 :@wuhanbbot
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全武汉安排妹子 : 😀😀😀😀 联系 : @wuhankebot 😀😀 😀😀😀😀😀 😀😀
❤1
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💐老师:#小兰 😦#光谷 😦课费: 600p 🐱电报: @Asd82538 ✏️频道: @asdhhhbbnm8899 🤖双向: @jahhbbot 报告榜 报告模板 报告提交 聊天群1 : @wuhanp 聊天群2 : @wuhannn 楼凤榜 : @wuhanbc 上榜员 :@wuhanbbot
❤1
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Showing the 12 most recent of 970 posts we hold for @wuhanbc. 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.
Posts edited after publishing
@wuhanbc edited 20 posts after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.
An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.
- First edit seen
- 24 August 2026
- Most recent edit
- 8 November 2026
Posts recorded as deleted after publishing
We recorded 3 posts on @wuhanbc as deleted — posts this register held that were missing from the channel’s public page on two separate reads, taken from different network addresses at least an hour apart.
A deletion is not wrongdoing. This register can see that a post it held is no longer on the channel’s public page, and when — not why. Expired ad placements, reposts, rotating links and corrections all look the same. This is a count of recorded detections, not an exact total: it misses deletions we could not see, because only a post we held and later re-read inside the page can be seen to go, and it may include a small number of wrong records. How this is measured.
- First seen missing
- 3 October 2026
- Most recent seen missing
- 30 October 2026
- Median time before seen missing
- 12 hours
- Seen missing in the last 30 days
- 2
Forward network
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.
Mentions
Named by 11 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.
@asdhhhbbnm8899 · 5411 post小妲己的后花园
@daji07666 · 461 post珊珊D+个人,先付,纯中
@fhhxh46 · 181 post极限反差😘😘财迷
@jxfc028899 · 7321 post琳琳在武汉
@linlin05020 · 9651 post彤彤的花园
@mmxgg520 · 1241 post小艾的朋友圈
@sjsbs123 · 2,0321 post矿泉水个人兼职95老师
@spayuo · 251 post悠悠的小花园
@suuaiai9 · 2221 post江城筱钰儿🌸
@xiaoyuer0404 · 6471 post洪山区光谷兼职(小兰花)
@zhi905420 · 7221 post
Names
Channels on the register whose handles appear in this channel's posts.
@wuhannn · 8,393688 posts武汉修车总群 ❶
@wuhanp · 71,273592 posts武汉修车频道 𖣔
@wuhanbg · 3,613505 posts中转频道
@yfzz888 · 1,65492 posts九九 个人开课
@NN22886 · 1,30320 posts可可~后花园
@keke5201314111 · 3,91119 posts小雯宝朋友圈
@xiaowenwende · 41716 posts欣悦儿的小窝
@whxiaoxinxin · 3,60714 posts子琪的小窝窝
@BB520115 · 4,09412 posts锦鲤的小屋(个人莞式服务) 🥰🥰🥰
@jili65 · 1,66011 posts天蝎ada的小屋🏠
@jiujiuada · 92911 posts青柠的后花园
@Wh52005 · 2,35711 posts莹莹的朋友圈
@yongyingde · 87211 posts洪山区光谷兼职(小兰花)
@zhi905420 · 72211 posts小野猫的小窝
@zmmzaayyy · 43711 posts温婉的后花园🌹
@wwg10789 · 1,17010 posts童瑶的后花园🌸
@yaoyao013469 · 23010 posts依依的世界🎀
@httpstmewMBnFk9ftbQzZDE1 · 2,6999 posts武汉国内首创根浴抓龙筋
@qaf645as · 2,4499 posts妍妍
@yzjqt · 6509 posts武汉白月光私影资料频道(重组版)
@byg77099 · 2,1358 posts光谷兼职个人开课
@meimei2698 · 8208 posts思思的朋友圈
@whsisi16888 · 8008 posts洪山甜甜的秘密花园
@kekels6 · 1,1927 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.
Handles this channel named that no longer answer
- Dead references
- 10
- handles named in this channel’s posts, vacant today
- Evidenced gone
- 10
- we ourselves saw one of these resolve, at some point
- Never seen alive
- 0
- vacant every time we have ever looked
@wuhanbc named 10 handles that resolve to nothing today. That is a fact about the reference, not necessarily a fact about the handle’s history — see the two groups below.
Most of these may never have existed as a live channel at all. A handle a channel names can be a typo, an aspirational name nobody registered, or a channel that was already gone before this one ever mentioned it. Unless a row below is marked evidenced, all we know is that it references a handle that is not a live channel today — not that anything “died”. How this is measured.
Evidenced gone
We ourselves saw each of these resolve to a real page at some point before it went vacant — a genuine, evidenced change, not an inference from absence.
named in 6 posts, 9 August 2026 – 8 November 2026 · confirmed gone 13 October 2026 (two independent sightings — see how we confirm a dead handle)evidenced
named in 2 posts, 4 September 2026 – 5 October 2026 · confirmed gone 16 October 2026 (two independent sightings — see how we confirm a dead handle)evidenced
named in 2 posts, 22 August 2026 – 25 August 2026 · confirmed gone 6 November 2026 (two independent sightings — see how we confirm a dead handle)evidenced
named in 2 posts, 22 August 2026 – 25 August 2026 · confirmed gone 7 November 2026 (two independent sightings — see how we confirm a dead handle)evidenced
named in 2 posts, 8 August 2026 – 8 August 2026 · confirmed gone 7 November 2026 (two independent sightings — see how we confirm a dead handle)evidenced
named in 1 post, 3 November 2026 – 3 November 2026 · confirmed gone 13 November 2026 (two independent sightings — see how we confirm a dead handle)evidenced
named in 1 post, 1 October 2026 – 1 October 2026 · confirmed gone 10 November 2026 (two independent sightings — see how we confirm a dead handle)evidenced
named in 1 post, 28 September 2026 – 28 September 2026 · confirmed gone 14 October 2026 (two independent sightings — see how we confirm a dead handle)evidenced
named in 1 post, 5 September 2026 – 5 September 2026 · confirmed gone 3 November 2026 (two independent sightings — see how we confirm a dead handle)evidenced
named in 1 post, 5 September 2026 – 5 September 2026 · confirmed gone 17 October 2026 (two independent sightings — see how we confirm a dead handle)evidenced
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 12 November 2026 — this entry's latest reading, not the date you are reading this.
“武汉楼凤榜 🅥” (@wuhanbc), 109,505 subscribers as measured 12 November 2026. Telegram Register, tgregister.com/channel/wuhanbc.
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.