#狼友投稿 我是小羊 给我🌿 主角:只撸管不做爱 用户名 @ZXP0806(水群用) 小号:舔逼哥 用户名 @ppazeq(出击、写报告用) 其他人物:某老师、大公鸡、本人 小🐑提醒: 1.老师防范此类刀法 2.再追着我咬,继续鞭尸
❤5👍2👎1

Channel
@suzhouyingying
On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Posts edited after publishing · Citations · Handles named that no longer answer · Cite this entry
27,896subscribers
+3,555 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 10,000–31,623.
| Telegram ID | -1003090367964 |
|---|---|
| Type | Channel |
| Username | @suzhouyingying |
| Created | Between 1 August 2025 and 31 October 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 5 September 2026 |
| Measurements held | 28 |
| Confirmed unchanged | 1 time, most recently 5 September 2026 |
| On Telegram | t.me/suzhouyingying |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 5 Sept 2026, 21:22 | 27,896 | +428 |
| 3 Sept 2026, 16:38 | 27,468 | +356 |
| 2 Sept 2026, 07:39 | 27,112 | +94 |
| 1 Sept 2026, 09:15 | 27,018 | +81 |
| 31 Aug 2026, 08:13 | 26,937 | +121 |
| 30 Aug 2026, 07:54 | 26,816 | +216 |
| 29 Aug 2026, 05:13 | 26,600 | +158 |
| 28 Aug 2026, 02:59 | 26,442 | +87 |
| 27 Aug 2026, 05:29 | 26,355 | +89 |
| 26 Aug 2026, 06:57 | 26,266 | +105 |
| 25 Aug 2026, 04:52 | 26,161 | +68 |
| 24 Aug 2026, 00:05 | 26,093 | +179 |
| 22 Aug 2026, 09:55 | 25,914 | +173 |
| 21 Aug 2026, 00:41 | 25,741 | +102 |
| 20 Aug 2026, 03:32 | 25,639 | +102 |
| 19 Aug 2026, 02:45 | 25,537 | +98 |
| 17 Aug 2026, 23:32 | 25,439 | +127 |
| 16 Aug 2026, 21:44 | 25,312 | +101 |
| 15 Aug 2026, 16:05 | 25,211 | +196 |
| 14 Aug 2026, 04:08 | 25,015 | first reading |
63 posts held, back to 2 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 62 pages of Telegram’s post history, 20 posts per page.
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 48 of 49 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 3 September 2026 |
|---|---|
| Posts held | 63 (2 August 2026 – 3 September 2026) |
| Views total | 393,740 |
| Reactions total | 18,779 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 4 Sept 2026, 12:38 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.
Measured directly from 10 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.
19,400 reactions across 61 posts, in 13 distinct kinds. The most used accounts for 20.5% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 3,970 | 20.5% | |
| 👏 | 3,623 | 18.7% | |
| 🎉 | 3,620 | 18.7% | |
| 🤩 | 3,600 | 18.6% | |
| 🔥 | 3,453 | 17.8% | |
| 💩 | 1,082 | 5.58% | |
| 🤡 | 16 | 0.082% | |
| 👍 | 14 | 0.072% | |
| 🤮 | 13 | 0.067% | |
| 😁 | 4 | 0.021% | |
| 🤣 | 3 | 0.015% | |
| 👎 | 1 | 0.005% | |
| 😴 | 1 | 0.005% |
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 62 of the 63 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 19,400 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 63 most recent posts we hold, published 2 August 2026 to 3 September 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.
#狼友投稿 我是小羊 给我🌿 主角:只撸管不做爱 用户名 @ZXP0806(水群用) 小号:舔逼哥 用户名 @ppazeq(出击、写报告用) 其他人物:某老师、大公鸡、本人 小🐑提醒: 1.老师防范此类刀法 2.再追着我咬,继续鞭尸
❤5👍2👎1
💕白金翰苏州男士SPA💕 相城-长桥-郭襄-甪直350💰 常熟-昆山-园区-太仓399 简介:(50分钟不限次数)五推服务,价格破底线,尺度破上限,69标配,可舌吻,裸毒龙。欢迎预定! 兄弟们可以邀请老师一起洗香香啦😂 可海选海选😆联系方式 @E2j01cc 双向 @ShuyuegeBot 交流群组链接
#外地瓜 @wocaibushi321 从其他地方嫖来一则新闻,大家吃瓜就好。 合肥一老师,自诉短短两个月遭遇各种事件例如:白嫖、抢钱、出血、假钱、出血等等,最后说是被鸡头带着打手给打了,老师直接去天地同寿了。 老师频道帖子: https://t.me/wwenw2321/263 来源: 广州战地记者 短评:16岁不给上榜是别人群生存的底线,至于那些明知不满16岁还去当舔狗的,现在去报警了一个都跑不掉了,大家不要当舔狗
❤1
没活儿了,抽个奖吧 📪抽奖说明: 周末来临可以先前往 苏州新秀榜 选个老师一起度过愉快的周末哦~还有拔得头筹优惠! 🎫 参与条件: 🎫 加入-苏州硬了么 🎫 加入-苏州新秀榜 🎫 加入-苏州树洞 🎫 加入-苏州硬了么公开性息 🎫 加入-苏州热花魁榜 🎁 奖品内容: 💰️ 100现金 × 1 💰️ 200现金 × 2 📅 开奖时间: 2026-09-08 00:00自动开奖
❤4
#硬了么 #桃花坞 关于“库洛米”否认自己是“奥运宝贝”“蔡文姬”事件 图1:事件起因,狼友“reset”投稿苏州库洛米是常州黑车蔡文姬后,老师出来回应。 图2:自证B干净,拍照发频道,然后被狼友发现阴蒂上有白色颗粒(老师解释是白带) 图3:奥运宝贝与库洛米个人频道照对比图。 图4:老师解释是盗图,说对比鼻子,(大家看一下有没有区别) 图5+视频:狼友扒出蔡文姬,奥运宝贝,库洛米纹身对比。(老师解释,都鸡巴姐们,纹到一起了,那我还说啥) 图6:常州狼友询问能否拍胸部自证或者拍姐们合照,证明三人共同纹了一个图,老师找了4个小时,没找到。 问题来了: 如果真像库洛米所说,自己被奥运宝贝和蔡文姬盗图,那么给予上榜的桃花坞管理干什么吃的?上榜不看人照,用的假照,走个过场?另外洞洞寻找奥运宝宝报告时发现狼友“田伯光”的报告配图居然是已经被实锤中介组织“糯米”的约课记录。我有时候真不知道这些管理怎么审的报告。(图7) 最后硬…
❤9🔥3
#狼友投稿 reset (不回私信,有问题频道留言) https://t.me/suzhouxinxiu/1704?single,洞洞 我投稿这个新秀榜老师,去年还是前年在常州开,叫蔡文姬,号称bbw实则大飞猪。说是女大应该是大专,身上还纹着前男友名字,机车的一比,蛇要加钱,自带了制服也要加钱,用她的也要加钱,最恶心的是贼脏。让洗一下说洗过了,然后衣服一脱b里还有残留的卫生纸,那天我还是头课,我直接恶心的阳痿跑路了,现在跑到苏州去居然还能给通过上榜,工兵还给好评,真气笑了😂她从常州走后改名字辗转几个地方了都,就是因为风评不行。 使用 @suzhouyingbot 自助投稿
❤7
杀死舔狗 舔狗你钱多自己给800约课行不行,把妹子舔出幻觉了。 AI换脸+三件套,她能开8吗?开不了,没那个实力。
🤣3
#狼友投稿 匿名 洞洞,匿匿,推上看到的一对夫妻,男方自称是绿毛🐢,喜欢看着bz跟单做,然后简单了解了一下,她们对单的要求是30以内且要是帅的,门槛费是388,活动费用是3000还需自带检测纸,我是认为30以内长得帅且有这个经济能力付得起这些钱完全没必要当单啊,不知道各位ly有相关经验吗?对此怎么看?以下是对应聊天记录 使用 @suzhouyingbot 自助投稿
❤1
#狼友投稿 匿名 最近看到苏州硬了么群因群利益被侵犯,利用媒体优势疯狂发文引战,对此我来说下我的看法。 一,前段时间有狼友投稿自己因担任多个群管理,被大总管约谈,不要挖墙脚,给其他群引流 ,后面没谈妥被踢群。于是硬了么群发了该狼友投稿,并内涵该群没有格局,标榜自己的群持开放态度,大家良性竞争。但没过几天又开始发稿喷苏州大学群是野鸡群,吐槽指责挖墙脚,这不是很矛盾么?再说了到底什么才算野鸡群?几年前,苏州还是乐园和新文化的时候,硬了么群刚冒出来不也是野鸡群么,也是靠挖墙脚,买僵尸粉起群的,怎么就忘本了呢 二,关于吐槽某群收费贵,薅老师羊毛搞活动,我没看懂,你不收费么?搞了个签到打卡的榜,每个月收老师一节课的上榜费,说是免费上榜,老师上榜后你就私聊老师开通打卡功能,你这么一说,有几个老师敢不交费的?看到其他群收得多,自己收得少,眼红了假装成正义使者指责其他群压榨老师,到底谁没有格局?还有吐槽茶馆群收费帮老师重复上榜提高影响力的,…
❤12
#狼友投稿 匿名 我才接触这个老师几天,自己也是萌新。本来老师那几天不接生意准备休息,但架不住我上头加钞能力,最后还是包天了。我当时想着,既然是出来让自己开心的,多花点钱也无所谓。 不过真正包天后发现,实际做的事情并没有多少,反而大部分时间都在聊天。虽然体验本身一般,但老师跟我讲的那些事情,反而让我觉得挺有意思。 我当初是看了一个“嫖娼大佬”的评价才找她的,评价写得特别夸张,什么“吞精”“什么事后萧”结果实际完全不是那么回事。我就问老师为什么不一样,她说了一句:“每天接触的人都不一样,都是生意。” 她还跟我讲过一个人,因为给她写过评价,就觉得自己帮她涨了粉、带来了生意,所以应该得到“报答”。后来甚至还要求老师把评价里那些实际上做不到的事情都给他做,最好还能打折。 老师当时就很无语,说自己每天基本都是满的,根本不缺那么点生意。那个人矮胖子短脖子,后来还用小号来约她,老师碍于人都来了没有拒绝,但之后就再也没接过他。 还有一个学生要…
❤9💩3
#狼友投稿 #茶馆 Bw 突然看到这个就想笑,为什么我当时投诉,不是处理老师的问题,而是处理提出问的人? 使用 @suzhouyingbot 自助投稿
❤2
苏州两大V开盒事件 最早得追述到今年4月 ⬆️(点击跳转) 省流:Bw主动挑事 时间线来到昨日 图1:起因 图2:PP询问树洞是否可以投稿,被洞拒 图3 4:继续嘴臭 图5:PP忍无可忍,要发视频和大头照。 图6:开盒进行中...... 图7:Bw被开了也不影响他继续嘴臭 图8:大V“武夫”点评 事后洞洞询问Bw会不会因为害怕注销账号。(图9) bw:I don’t care
❤4
Showing the 12 most recent of 63 posts we hold for @suzhouyingying. 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.
@suzhouyingying edited 4 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.
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.
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.
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.
@suzhouyingying named 1 handle 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.
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.
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 5 September 2026 — this entry's latest reading, not the date you are reading this.
“苏州树洞” (@suzhouyingying), 27,896 subscribers as measured 5 September 2026. Telegram Register, tgregister.com/channel/suzhouyingying.
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.