https://t.me/shenshengchujian/1644 今天和明天可约鸭❤️ @Yingying7897 3号就休息啦

Channel
相见欢名录
@shenshengchujian
On this record: Topic · Growth · Engagement · What this channel posts · Posts · Citations · Cite this entry
11,311subscribers
-964 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 10,000–31,623.
Register entry
| Telegram ID | -1002859449398 |
|---|---|
| Type | Channel |
| Username | @shenshengchujian |
| Created | Between 1 June 2025 and 30 September 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 18 September 2026 |
| Measurements held | 33 |
| Confirmed unchanged | 1 time, most recently 18 September 2026 |
| On Telegram | t.me/shenshengchujian |
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 11 September 2026 and assigned it the closest of 31 fixed categories, at 89% 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 |
|---|---|---|
| 18 Sept 2026, 01:59 | 11,311 | +41 |
| 16 Sept 2026, 00:39 | 11,270 | -19 |
| 14 Sept 2026, 07:58 | 11,289 | +2 |
| 12 Sept 2026, 14:16 | 11,287 | -18 |
| 10 Sept 2026, 11:56 | 11,305 | -51 |
| 7 Sept 2026, 04:38 | 11,356 | -3 |
| 4 Sept 2026, 12:00 | 11,359 | +8 |
| 3 Sept 2026, 00:03 | 11,351 | -18 |
| 1 Sept 2026, 22:25 | 11,369 | -146 |
| 31 Aug 2026, 21:47 | 11,515 | -23 |
| 30 Aug 2026, 22:07 | 11,538 | -11 |
| 29 Aug 2026, 21:43 | 11,549 | -24 |
| 28 Aug 2026, 19:14 | 11,573 | +23 |
| 27 Aug 2026, 22:25 | 11,550 | +27 |
| 26 Aug 2026, 19:04 | 11,523 | +11 |
| 25 Aug 2026, 17:47 | 11,512 | -36 |
| 24 Aug 2026, 16:19 | 11,548 | +2 |
| 23 Aug 2026, 03:04 | 11,546 | +37 |
| 21 Aug 2026, 13:04 | 11,509 | +14 |
| 20 Aug 2026, 11:06 | 11,495 | first reading |
Engagement
26 posts held, back to 5 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 45 pages of Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 7.40%
- avg views ÷ 11,311 subscribers
- Avg views / post
- 837
- 4 posts measured
- Reaction rate
- —
- this channel exposes no reaction counts
- Posts in window
- 4
- of 26 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.
| Window | Rolling 30 days · latest post in window 1 September 2026 |
|---|---|
| Posts held | 26 (5 August 2026 – 1 September 2026) |
| Views total | 3,347 |
| Reactions total | — |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 3 Sept 2026, 00:45 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
- 1m 02s
- Average length
- 10s
Measured directly from 6 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.
Recent posts
🎀 老师:#南山星星🩷 🎀 联系 :@xingxing0622 🎀 特点 :#情绪价值🎈 #女友感 #天然胸D✈️ #舌吻管饱 #颜值很高 #细枝硕果 #大蟒蛇 #水多反馈好 身材好颜值高女友感强 服务态度很好 最喜欢的老师没有之一,人照十成真的好看,颜值百看不腻。身材也是熟地大波,胸那么饱满屁股有肉的同时,腰和腿还那么瘦。 已经反了十次多的老师,情绪价值拉满,星星很爱聊天和谁都能聊开,而且很有能量,开朗爱笑很感染人。服务也是很顶,水中潇舌吻口的时间长,而且还敏感下面摸一摸就有水。 每次去完隔两天都会再想去,聊天很开心,床上舌吻到饱,反馈也很好,女上很会摇,身材很好,很推荐的老师,各方面都很好,有机会还会一直去的。
🎀 老师:#小柔 🎀 地区:#坂田🩷 🎀 联系 :@bantianxiaorou1 🎀 特点 :#艳舞表演🎈 #服务用心 #身材苗条✈️ #紧致反馈好 #态度好 #制服丝袜 #人照一致 🎀 课费:1000💎(45) 1800(90) 🎀 服务:#胸推 #六九 #艳舞 #共浴 🎀 报告:https://t.me/xueshuqu/776
🎀 老师:#南山雨彤🩷 🎀 联系 :@SZlingling7 🎀 特点 :#服务很好🎈 #水中潇 #前凸后翘✈️ #浴室服务多 #态度好 #人照一致 #情绪价值高 #主动热情 身材不错服务很多 主动热情体验好 老师人照差不多,身材不错屁股翘,服务花样多,体验很不错也不流程化,会让先挑选衣服,情趣很多看的眼花缭乱的。浴室服务很舒服,涂上沐浴露正面背面的胸推,还有水中潇,在浴室就很爽。 床上服务也不错,手口并用很色情也很舒服,舌吻管饱,弔感很不错,女上也很会摇。老师态度超级好,还会问有没有需要改进的地方,然后还在学习新的服务,冰火两重天,还有剧情演绎之类的,颜值服务都不错的老师,推荐。
🎀 老师:#南山书窈🩷 🎀 联系 :@shuyao088 🎀 特点 :#大长腿🎈 #身高173 #身材超好✈️ #弔感无敌 #敏感水多 #人照一致 #情绪价值高 #反馈好 大长腿身材超好 敏感水多弔感超级好 书窈人照九成身材很好,裸身高173左右,腿细长笔直腿控很满足,说话声音很甜,态度很好在沙发上就亲吻起来。 床上很配合口活也很舒服,操盘起来很舒服,躺着享受也可以,一双大长腿摆在床上着实诱人。最令人难忘的是书窈下面的紧致感,一直觉得敏感的会是小只马,没想到书窈下面那么紧致敏感,真的是几下之后书窈就会猛烈收缩,紧紧的夹住,哪怕去了这么多老师,这份紧致感和收缩吸紧的感觉也很少遇到。 书窈高潮好几次,换姿势的时候摸下面真的是全是水,都流到大腿了,最后在老师娇声求饶中结束。反馈很好弔感很难忘的大长腿老师,冲这份反馈还会去的。
🎀 老师:#梓菡 🎀 地区:#南山🩷 🎀 联系 :@zixin221 🎀 特点 :#皮肤白🎈 #天然胸 #身材好✈️ #天然无整 #声音甜 #性格好 #服务认真 #人照一致 🎀 课费:800💎(60) 1600(90) 🎀 服务:#舌吻 #六九 #口爆 #共浴
🎀 老师:#南山莹莹🩷 🎀 联系 :@Yingying7897 🎀 特点 :#白嫩可爱🎈 #无纹身 #情绪价值✈️ #天然胸 #身材好 #真人颜值高 #声音甜妹 #反馈超好 颜值性格都很可爱 服务认真反馈很好 超短时间的二反,很喜欢的甜妹,真人颜值比照片高,性格很可爱情绪价值很到位。胸盈盈一握很软很好摸,屁股也圆圆的后入很舒服。舌吻管饱,和香香软软的妹子舌吻真的是享受 服务很认真很配合,娇羞反应很可爱,舌吻个够用手抚摸下面,莹莹还会自己用手找感觉,口的很舒服包裹感好没有齿感,下面很紧弔感超级好,妹妹很嫩边做边舌吻好爽 服务态度好不催时间,颜值身材都很喜欢,聊天很开心,真是一个不错的老师,还会再去的。
🎀 老师:#南山林柏慧🩷 🎀 联系 :@linbaihui088 🎀 特点 :#潮喷水娃🎈 #水量超多 #AV女主✈️ #天然D胸 #大蟒蛇 #反馈很强 #敏感风骚 色情水娃水超多 敏感反馈足配合很好 超能喷水的水娃回来开课了,依旧是超能喷水,一场战斗下来喷了五六次,口活超好服务很棒,每次感觉都是被榨干,喜欢骚气水娃的推荐去体验。而且腿长胸大,身材也是很不错的。
🎀 老师:#南山莹莹🩷 🎀 联系 :@Yingying7897 🎀 特点 :#白嫩可爱🎈 #无纹身 #情绪价值✈️ #天然胸 #身材好 #真人颜值高 #声音甜妹 身材很不错颜值可爱的新人老师 反馈很好 老师照片看着很嫩身材不错,真人感觉颜值更高一下就被颜值吸引了,莹莹的金色高跟鞋显着玉足也很好看,身材挺不错比例很好,胸B➕很软很好摸 服务都很好,共浴洗的很仔细,准备了几套制服,相处起来很舒服,妹妹动作声音都好可爱,床上也很主动,舌吻很爽反馈也好,声音甜会叫爸爸 真人颜值挺好挺可爱的嫩妹,05年身材前凸后翘,床上反馈真实,很不错的甜妹,可爱甜美身材好,很推荐
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🎀 老师:#莹莹 🎀 地区:#南山🩷 🎀 联系 :@Yingying7897 🎀 特点 :#白嫩可爱🎈 #无纹身 #情绪价值✈️ #天然胸 #身材好 🎀 课费:1100💎(60) 2000(90) 🎀 服务:#舌吻 #共浴 #制服 #丝袜
🎀 老师:#千雪 🎀 地区:#宝安🩷 🎀 联系 :@SzQianxue8 🎀 特点 :#天然D胸🎈 #精油spa #顶级服务✈️ #情绪价值 #身材好 🎀 课费:800💎(60) 1500(100) 🎀 服务:#舌吻 #六九 #胸推 #丝袜
Showing the 12 most recent of 26 posts we hold for @shenshengchujian. 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.
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 7 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.
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 18 September 2026 — this entry's latest reading, not the date you are reading this.
“相见欢名录” (@shenshengchujian), 11,311 subscribers as measured 18 September 2026. Telegram Register, tgregister.com/channel/shenshengchujian.
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.