他忍不住了,脱掉裤子,把已经硬得发疼的鸡巴抵在她湿滑的逼口,腰一沉,整根没入。“南枝……我好喜欢你……”他一边干一边说,动作又深又急。 南枝被他顶得身体轻轻晃动,可表情始终平静。

Channel
匿名树洞北京
@shudongbeijing
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Handles named that no longer answer · Cite this entry
31,518subscribers
+560 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 10,000–31,623.
Register entry
| Telegram ID | -1002589909906 |
|---|---|
| Type | Channel |
| Usernames | @shudongbeijing @shudongbj |
| Description | 是你的情绪垃圾桶🤮~ 请勿刷屏、键政、发广告,有防刷!(仅限修车那点事❗️) 发给树洞机器人的任何消息,将转发到对应频道~ #修车 #吃瓜 #匿名 #秘密 #树洞 #北京 🌲导航: @sdindex 🗺修车地图: @shudongmap 🔍洞洞搜: @dongdongso_bot 🤖树洞主: @shudongadmin_bot |
| Created | Between 1 March 2025 and 31 July 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 6 November 2026 |
| Measurements held | 119 |
| Confirmed unchanged | 1 time, most recently 6 November 2026 |
| On Telegram | t.me/shudongbeijing |
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 87% 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 |
|---|---|---|
| 6 Nov 2026, 09:20 | 31,518 | -43 |
| 6 Nov 2026, 00:06 | 31,561 | -58 |
| 5 Nov 2026, 07:56 | 31,619 | -83 |
| 4 Nov 2026, 21:00 | 31,702 | -55 |
| 4 Nov 2026, 03:59 | 31,757 | -40 |
| 3 Nov 2026, 23:47 | 31,797 | -35 |
| 3 Nov 2026, 05:01 | 31,832 | +145 |
| 2 Nov 2026, 22:18 | 31,687 | +132 |
| 2 Nov 2026, 04:26 | 31,555 | -14 |
| 1 Nov 2026, 21:09 | 31,569 | +42 |
| 1 Nov 2026, 00:46 | 31,527 | no change |
| 31 Oct 2026, 19:40 | 31,527 | +97 |
| 30 Oct 2026, 22:09 | 31,430 | no change |
| 30 Oct 2026, 18:29 | 31,430 | -159 |
| 29 Oct 2026, 20:46 | 31,589 | no change |
| 29 Oct 2026, 19:49 | 31,589 | -88 |
| 29 Oct 2026, 00:00 | 31,677 | -15 |
| 28 Oct 2026, 17:19 | 31,692 | -73 |
| 28 Oct 2026, 01:28 | 31,765 | +37 |
| 27 Oct 2026, 15:57 | 31,728 | first reading |
Engagement
3,044 posts held, back to 7 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 156 pages of Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 0.346%
- avg views ÷ 31,518 subscribers
- Avg views / post
- 109
- 1,142 posts measured
- Reaction rate
- 1.32%
- reactions ÷ views · ER floor
- Posts in window
- 1,142
- of 3,044 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 42 of 1,142 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 6 November 2026 |
|---|---|
| Posts held | 3,044 (7 August 2026 – 6 November 2026) |
| Views total | 124,441 |
| Reactions total | 82 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 6 Nov 2026, 10:03 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
- ≈450
- Videos
- ≈335
- Links
- ≈33,500
Lifetime counters from Telegram’s own channel header, read 6 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.
Reaction mix
79 reactions across 31 posts, in 5 distinct kinds. The most used accounts for 46.8% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 👍 | 37 | 46.8% | |
| ❤ | 23 | 29.1% | |
| 💩 | 12 | 15.2% | |
| 👎 | 6 | 7.59% | |
| 👌 | 1 | 1.27% |
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 39 of the 1,000 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 79 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 1,000 most recent posts we hold (the sample is capped at 1,000), published 11 October 2026 to 6 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 1,142 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).
他的舌头很认真,从会阴一路舔到阴蒂,把那颗小小的肉粒含进嘴里用力吮吸。南枝发出细细的喘息,可眼神始终有些游离。他伸进两根手指,在她逼里搅动,试图找到她的敏感点,可南枝只是轻轻哼了几声,并没有真正动情。
那天晚上,大祭司把她约到酒店。刚进门他就把她按在门板上亲,手伸进她裙子里,摸到那处已经有点湿。南枝没有拒绝,只是懒洋洋地靠着墙,任他脱自己的衣服。 大祭司把她抱到床上,跪下去先舔。
大祭司喜欢南枝很久了。 他是南大出身的高学历,在圈里算有点身份,可只要一见到南枝,就变成最卑微的那一个。他愿意为她花钱、为她写长篇反馈、为她在群里护航,甚至愿意把她的名字刻在心里。可南枝只把他当一个普通客人。
拉倒吧 3k的大圈又不是没有自己开的20 25就可以,大圈3k 然后有的中介25 自开20 最后照片都是p的
戴套的主要作用是避孕,哈哈哈哈,所以才叫避孕套,哈哈哈哈哈😂
出击不安全 安全不出击
戴套能抵挡住么
几百根🐍,可能被传染一切可以被传染的病
https://t.me/shudongbeijing/203690 长春好玩的还都没开。
太哈人了,肮脏😥
有些狼友脑子真的进水了,老师得了梅毒,还和她啪啪,真是蠢爆了。要不是蜀黍进来当场抓了,又不知道多少大冤种被祸害了。
Showing the 12 most recent of 3,044 posts we hold for @shudongbeijing. 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 3 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.
Names
Channels on the register whose handles appear in this channel's posts.
@BST88999 · 2,70470 posts树洞图片区
@shudongphoto · 12,15447 posts树洞导航
@sdindex · 12,18929 posts北京【洞洞】男群
@bjddnq · 4,52325 posts广州【洞洞】男群
@gzddnq · 2,99025 posts上海【洞洞】男群
@shddnq · 2,89325 posts深圳【洞洞】男群
@szddnq · 3,11425 posts树洞百科Wiki
@shudongbaike4 · 2,77316 posts树洞雷报北京
@shudongleibao_bj · 2,33916 posts树洞雷报广州
@shudongleibao_gz · 2,44016 posts树洞雷报杭州
@shudongleibao_hz · 1,78616 posts树洞雷报上海
@shudongleibao_sh · 2,01516 posts树洞雷报深圳
@shudongleibao_sz · 2,14116 posts树洞情报站
@shudongqingbao2 · 1,53316 posts树洞【实时】修车地图
@shudongmap · 5,1199 posts理学家
@lixuejia_1 · 77 posts天津意大利风情街🅢
@anyang2025 · 75,5901 post局内人·北京群聊吃瓜
@bj_group_daily · 1541 post北京凤楼会所
@dushmlap · 21 post北京女姬队
@huytj66 · 21,0591 post匿名树洞上海
@shudongshanghai · 10,1761 post匿名树洞深圳
@shudongsz · 15,0891 post
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
- 2
- handles named in this channel’s posts, vacant today
- Evidenced gone
- 0
- we ourselves saw one of these resolve, at some point
- Never seen alive
- 2
- vacant every time we have ever looked
@shudongbeijing named 2 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.
Never seen alive
References a handle that is not a live channel — we have no record it ever was one.
named in 6 posts, 16 August 2026 – 19 October 2026
named in 1 post, 11 October 2026 – 11 October 2026
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 6 November 2026 — this entry's latest reading, not the date you are reading this.
“匿名树洞北京” (@shudongbeijing), 31,518 subscribers as measured 6 November 2026. Telegram Register, tgregister.com/channel/shudongbeijing.
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.