Telegram RegisterThe public register of Telegram
Telegram profile photo for 💃🏻站街快餐👠spa会所

Channel

💃🏻站街快餐👠spa会所

@zhanjieZJ

On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry

23,027subscribers

+6,447 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-1002693571272
TypeChannel
Username@zhanjieZJ
CreatedBetween 1 April 2025 and 31 July 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live3 October 2026
Measurements held35
Confirmed unchanged1 time, most recently 3 October 2026
On Telegramt.me/zhanjieZJ

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 10 September 2026 and assigned it the closest of 31 fixed categories, at 80% 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

16,58023,02719,803.57 August 2026 — 16,580 subscribers7 August 2026 — 16,580 subscribers8 August 2026 — 16,654 subscribers9 August 2026 — 16,721 subscribers10 August 2026 — 16,786 subscribers11 August 2026 — 16,861 subscribers12 August 2026 — 17,017 subscribers13 August 2026 — 17,099 subscribers15 August 2026 — 17,259 subscribers16 August 2026 — 17,438 subscribers17 August 2026 — 17,564 subscribers18 August 2026 — 17,665 subscribers19 August 2026 — 17,781 subscribers20 August 2026 — 17,905 subscribers22 August 2026 — 18,103 subscribers24 August 2026 — 18,422 subscribers25 August 2026 — 18,574 subscribers26 August 2026 — 18,766 subscribers27 August 2026 — 18,902 subscribers28 August 2026 — 19,011 subscribers29 August 2026 — 19,174 subscribers30 August 2026 — 19,371 subscribers31 August 2026 — 19,507 subscribers1 September 2026 — 19,624 subscribers2 September 2026 — 19,766 subscribers3 September 2026 — 19,936 subscribers5 September 2026 — 20,169 subscribers8 September 2026 — 20,482 subscribers11 September 2026 — 20,786 subscribers13 September 2026 — 20,997 subscribers14 September 2026 — 21,156 subscribers16 September 2026 — 21,296 subscribers18 September 2026 — 21,506 subscribers25 September 2026 — 22,033 subscribers3 October 2026 — 23,027 subscribers7 August 20263 October 2026
35 measurements spanning 57 days, net +6,447. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 15,613–23,994 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 35
Measured (UTC)SubscribersChange
3 Oct 2026, 23:5623,027+994
25 Sept 2026, 04:5622,033+527
18 Sept 2026, 21:3621,506+210
16 Sept 2026, 10:3821,296+140
14 Sept 2026, 16:4221,156+159
13 Sept 2026, 05:3820,997+211
11 Sept 2026, 05:5820,786+304
8 Sept 2026, 10:0120,482+313
5 Sept 2026, 08:1720,169+233
3 Sept 2026, 14:4119,936+170
2 Sept 2026, 04:2419,766+142
1 Sept 2026, 06:5619,624+117
31 Aug 2026, 06:5519,507+136
30 Aug 2026, 07:4619,371+197
29 Aug 2026, 05:5319,174+163
28 Aug 2026, 09:0319,011+109
27 Aug 2026, 07:4618,902+136
26 Aug 2026, 08:3318,766+192
25 Aug 2026, 08:1218,574+152
24 Aug 2026, 05:0618,422first reading

Engagement

539 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 63 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
2.28%
avg views ÷ 23,027 subscribers
Avg views / post
526
50 posts measured
Reaction rate
0.184%
reactions ÷ views · ER floor
Posts in window
50
of 539 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 16 of 50 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 30 September 2026
Posts held539 (7 August 2026 – 30 September 2026)
Views total26,279
Reactions total18
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken30 Sept 2026, 06:00 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 37s
Average length
8s

Measured directly from 12 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

90 reactions across 72 posts, in 3 distinct kinds. The most used accounts for 96.7% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤8796.7%
👎22.22%
🔥11.11%

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 108 of the 539 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 90 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 539 most recent posts we hold, published 7 August 2026 to 30 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.

Recent posts

30 Sept 2026, 05:20 UTC37 viewsread 30 September 2026
Photo

🏆美加墨世界杯🏆足球盛宴震撼来袭⚽️ 首存赠送100% 尊享VIP永久享受权益 超高返水1.2% 💎返水无上限无需流水、电子、真人0审核包出款 💎免实名、无需绑定手机号码 💎USDT存取款秒到账、大额无忧 🎰体育🎰真人🎰电子🎰棋牌🎰捕鱼 【 天天体育🌐官网 26299.xyz 】 🔰群主强烈推荐信誉大平台✅一起玩赚世界杯🔥

29 Sept 2026, 11:07 UTC≈1,010 views1 reactionsread 30 September 2026

#西安 #舞厅 周六晚上21点左右直接杀向人气舞厅简爱舞厅,门票20元,目前舞厅女的差不多有一百个左右吧,在靠近厕所边上的左手边有些是舞厅直接打炮的舞女,但是普遍年纪偏大,有两三个还行,但是开价都是五六百一次,不值的,还不如吉祥村200一次的妹颜值高,纱舞是一亮四黑,亮曲选人,进去沙四曲,给舞女40块,一首歌三分钟十元,基本上大多数舞女都可以摸奶子,下面基本上很少能方便摸毛毛的,所以只适合搓奶,目前简爱舞厅没有发现舞池站桩,都是舞女开价约出去打炮,十来二十分钟左右回来,所以不建议在舞厅找舞女打炮,24点出简爱舞厅后直接杀向吉祥村找小旅馆里面的精神小妹打炮,一般开价都是200块十五分钟左右,认准旁边有绝味鸭脖与鸡柳大人两家店的小巷子进去,里面应该有十家左右的店,门口有鸡头问你要不要找妹,直接跟着进去看妹,能看上就直接找,没看上就换下一家继续看妹,我找了个20岁大长腿精神小妹出货二百块,先给钱,后打炮,结束直接走人回去休息,明天赶…

❤1

29 Sept 2026, 11:07 UTC895 viewsread 30 September 2026

#西安 #扫街 路过罗家寨,从西门旁边进,就是网吧左边那个街口,直走,晚上七八点去的,嫩嫩的有三四个,穿的骚骚的,心动,服务一般般,胜在年轻身材好,大战三百回合,回归圣人模式,回家休息。 ❗️投稿联系👉 . 频道为部分更新展示,更多详情进群搜索城市名查询: @waiwei31655

29 Sept 2026, 11:07 UTC828 views1 reactionsread 30 September 2026

#西安 #舞厅 从西安回来也一段时间了,闲着没事就说说8月底去红河谷、简爱、金卡罗和吉祥村的事。去了4天,每天各个舞厅都逛一遍,所以为了朋友们看的方便,我就一个一个介绍 首先说简爱,我就住旁边酒店所以非常方便,下午1点楼下就一堆人做外面排队。后来听说1点半之前去可以免费。我就跟着人群进去了。对于一个初来乍到的人我比较谦虚,问了问情况,里面老哥也热情回答。但是现在舞池还没有女的。就玩玩手机一直到2点才陆陆续续有女的出现,先按兵不动看看情况。还看到了厕所那一排站桩的性价比不高。随后看到靠吧台那边柱子有个大概20出头的吧穿个抹胸进入我的眼帘,拉进舞池,身材真好。问了一下喜欢锻炼。然后头就埋进脖子随着舞曲的律动慢慢的吮吸,那锁骨真的性感。第二天是周末日太多了火车站都没这么多人。找了一个穿防晒衣露半边胸的靠着墙根慢慢摸。兄弟我早做好准备了,内裤不穿,外面就穿一条非常薄软的大裤头。硬起来直接让她夹着,后来她把手从边上掏进去套弄,我吸着她的…

❤1

29 Sept 2026, 11:07 UTC611 viewsread 30 September 2026

#西安 #探店 田家湾 中午11点多就有,大概三个年轻的,6个老的站街模式 三官庙 一排足疗店,路口有两个年轻点的,其他老,去了一个150吹做,没搞出来,也不加重 简家村 人数挺多,站在门口,没看到年轻的,好像有一个说100qt 沙井村 站街的不多,没看到年轻的,有一两个36左右的,其他太老了 长里村 一排足疗店,分不清是正规还是有项目的,旁边倒是有个阿姨拉客后面屋里有个鸡 罗家寨 不少很年轻的,不少新疆面孔的,下午和晚上有 袁旗寨 都在屋门口坐着,年轻的玩手机,年纪大的吆喝,sf在嗑瓜子 . 频道为部分更新展示,更多详情进群搜索城市名查询: @waiwei31655

29 Sept 2026, 11:07 UTC584 viewsread 30 September 2026

#西安 #探店 南康新村西边的门面御足阁还是御足缘来着,以前就去过好几次,因为有个年轻的微胖妹在,那女娃还是确实不错,身材高挑,微胖,胸也不错,之前帖子写过有一次正在做他对象打电话过来我让接妹子不敢接,这次又去了那个妹子不在,有个少妇,绑马尾看着比较精干,身材不错就选她了,还是原来的套路进到后面的民房里,脱衣服口几下开干,比较配合,干完了直接从后门就走了,也不用再从店里出去,总体来说安全性较高,朋友们去吧,对了那一条街上还有个紫云阁足浴,238好像是飞机,但是跟技师聊的好的话可以口暴,我试过一次,活不错,再其他的就看自己本事啦,应该也能叫出去 . 频道为部分更新展示,更多详情进群搜索城市名查询: @waiwei31655

29 Sept 2026, 11:07 UTC545 views1 reactionsread 30 September 2026

#西安 #探店 雁塔长安西路紫郡长安楼上,客服xx24gq,深夜卧床辗转难眠,身体燥热,身体状态告诉我该出击了,在这个特殊时期靠谱最重要。于是毫不犹豫联系经理迅速安排,苦了谁也不能苦小弟弟。到达地点上电梯、换鞋后直奔包厢。并心中牢记选大胸妹窍诀,但由于去的时间在出击高峰时段,妹妹较少,但进来的第一个妹妹完全符合大胸妹特征,毫不犹豫确定,脱衣后微胖,体白,胸真的是又大又白又嫩,目测e到f,直接上手,触感又软又嫩,都舍不得捏。褪衣沐浴后正式开始,上手互摸,全身游走,撕丝袜。磨蹭一会后躺下让妹妹开始服务,第一局在妹妹的服务下快速缴枪,进入中场休息,喝水,抽事后烟,歇息片刻后妹妹开始按摩,胸推,漫游,舔蛋蛋,奈何弟弟硬不起来,于是躺床上摸着妹妹的胸,并让妹妹舔咪咪,在气氛的烘托和不断地舔舐下弟弟重整雄风,屹立不倒。我一手摸胸,一手摸屁股,舌头快速挑动着大胸妹的小痘痘,在一声声的小哥哥,姐夫和淫叫声中逐渐缴枪。结束后躺在床上休息。奈何时…

❤1

29 Sept 2026, 11:06 UTC512 views1 reactionsread 30 September 2026

#武汉 #探店 金桥大道20号中胜村K1地块2号酒店式公寓、3号 商业栋1-3层望月庭spa,作为出差在武汉的第一次探店,这家spa总体感觉不错。环境上来说,没有杭州、上海spa环境那么奢华,但也很干净卫生,单个房间面积也还行(补充一下根据后续武汉体验来说,可能武汉spa环境都是这样,不同地方标准不同)。服务还行该有的都有,上来直接干正事,没有划水行为没有偷钟的行为,服务这个见仁见智,我认为是OK的。最后说一下价格,不到400的价格一水,我认为是性价比拉满。 . 频道为部分更新展示,更多详情进群搜索城市名查询: @waiwei31655

❤1

29 Sept 2026, 11:06 UTC504 viewsread 30 September 2026

#武汉 #扫街 平安路,地图搜索 速豪汽车服务,紧挨着汽修的这家店,狼友推荐的一个南湖气质嫂子,按地址到一个汽修店,挨着两家都是。紧挨着这家。一个带着眼睛的小嫂子,属于气质型。问有没有口,很勉强的说带膜口。上二楼服务。口了半分钟就开始躺下让小狼动。口的比较敷衍的。不过下面不怎么松,艹了十分钟也没催,匆匆出货结束 . 频道为部分更新展示,更多详情进群搜索城市名查询: @waiwei31655

29 Sept 2026, 11:06 UTC479 viewsread 30 September 2026
Photo

#武汉 #扫街 今天去六渡桥修相机,返回途经长堤街。发现两家店铺里面有不少长腿包臀妹妹,其中一家挂着采耳招牌,具体情况不详,感觉是挂羊头卖狗肉。可自行去试雷,欢迎有了解情况的网友科普下。就是途中中百超市旁边。 . 频道为部分更新展示,更多详情进群搜索城市名查询: @waiwei31655

29 Sept 2026, 11:06 UTC486 viewsread 30 September 2026

#武汉 #扫街 青山区黄州街与工业三路交汇十字路口,沿黄州街走万通手机维修旁边无字招牌店,第二家在肥肠鱼川菜馆旁边无字招牌店,第三家在第二家正对面无字招牌店,来到黄州街,右手边第一家店有两个妹子,一个年轻一点感觉20多,一个30左右,两位穿着都还比较年轻时尚,先点了年轻一点的那个,身材微微胖,该有肉的地方都有肉,下面💧多还比较紧,🌿的很舒服完美炮架,服务态度也很好可以给8分。然后试了另一个小嫂子骨感身材长相还可以,下面比年轻的那个松一些,态度也没年轻的积极,体验一般,🌿死鱼的感觉综合只能给5分。这家店完了继续往前走,又看见一家无字招牌店,进去一看还是两个,黑白双煞,一个黑色包臀裙高跟鞋,一个白色运动装头戴发带,小腿白丝配小白鞋,穿搭还比较满意,但两个应该都是30+的小少妇了,年龄比第一家店要大一点,黑色身材容貌一般不是我的菜没有点,白色的穿搭更打动我,容貌也没有那么老气,可以一试,进去脱衣也是骨感身材,下面比较松,🌿起来感觉一…

29 Sept 2026, 11:06 UTC431 views0 reactionsread 30 September 2026
Photo

最近连玩一个星期了,这个汤泉足道88号本来从良了,最近又回来上班了,所以发了消息约了个94,长相身材都没得说,94明星技师消费369,舔蛋舔弟弟真毒龙全裸69基本都玩了,最后69打的时候扣着比浪叫属实销魂(69的时候可舔可扣)美中不足不能舌吻,妹子说化妆要很久,怕弄花了不好补(图片朋友圈偷得对版) 汤泉还有个22号普通技师,玩94消费299,也是真毒龙,舌头软的很又灵活,顶也是真往里顶,挺卖力的,少妇身材也还行,全裸舔蛋啥的都能来 66也试过,上次舌了,但做的果冻毒龙,能全裸魔棒 玩的几个技师基本都是做94,消费也不高299-369,性价比还可以 微信 quan168168a . 频道为部分更新展示,更多详情进群搜索城市名查询: @waiwei31655

Showing the 12 most recent of 539 posts we hold for @zhanjieZJ. 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

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 3 October 2026 — this entry's latest reading, not the date you are reading this.

“💃🏻站街快餐👠spa会所” (@zhanjieZJ), 23,027 subscribers as measured 3 October 2026. Telegram Register, tgregister.com/channel/zhanjieZJ.

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.