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Channel

常州⌛黄金门票

@xxlmspa

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

7,372subscribers

-306 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 3,162–10,000.

Register entry

Telegram ID-1002139182055
TypeChannel
Username@xxlmspa
CreatedBetween 1 November 2023 and 31 May 2024— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live30 August 2026
Measurements held10
Confirmed unchanged1 time, most recently 30 August 2026
On Telegramt.me/xxlmspa

Growth

7,3727,6787,5257 August 2026 — 7,678 subscribers7 August 2026 — 7,678 subscribers8 August 2026 — 7,660 subscribers11 August 2026 — 7,616 subscribers14 August 2026 — 7,572 subscribers17 August 2026 — 7,518 subscribers20 August 2026 — 7,490 subscribers24 August 2026 — 7,435 subscribers27 August 2026 — 7,398 subscribers30 August 2026 — 7,372 subscribers7 August 202630 August 2026
10 measurements spanning 22 days, net -306. 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 7,326–7,724 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
30 Aug 2026, 03:447,372-26
27 Aug 2026, 12:137,398-37
24 Aug 2026, 07:447,435-55
20 Aug 2026, 11:137,490-28
17 Aug 2026, 20:547,518-54
14 Aug 2026, 20:187,572-44
11 Aug 2026, 08:427,616-44
8 Aug 2026, 08:427,660-18
7 Aug 2026, 17:317,678no change
7 Aug 2026, 17:217,678first reading

Engagement

6 posts held, back to 3 April 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 15 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
18.5%
avg views ÷ 7,372 subscribers
Avg views / post
1,370
2 posts measured
Reaction rate
0.11%
reactions ÷ views · ER floor
Posts in window
2
of 6 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.

What these figures were computed from
WindowRolling 30 days · latest post in window 10 August 2026
Posts held6 (3 April 202610 August 2026)
Views total2,730
Reactions total3
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken28 Aug 2026, 23:16 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
21s
Average length
11s

Measured directly from 2 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

48 reactions across 6 posts, in 3 distinct kinds. The most used accounts for 95.8% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
4695.8%
👍12.08%
👎12.08%

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 6 of the 6 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 48reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 6 most recent posts we hold, published 3 April 2026 to 10 August 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

10 Aug 2026, 06:31 UTC≈1,180 views2 reactionsread 28 August 2026
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《常州新北区独家5T剧情会所》 ⚡⚡主打颜值 服务 环境 安全为一体的高端私密会所 ⚡⚡长期靠谱安全稳定,不办卡,不套路 ❤{ 各种类型 } - ⚡⚡⚡⚡ 🐷专业技师、御姐、萝莉、少女、二次元嫩妹 📱📱📱📱📱📱📱📱📱📱📱📱 ❤{ 各种剧本 } - 🤣😂😆🥹😂 🐷女仆与主人 、空姐与乘客 、学生与老师 、护士与病人、秘书与上司、SM女王、 ……等等可自由选择 ! 🫤😬🤣🤣 7⃣5⃣6⃣🫥 🤔 联系客服:@klquueryp 微信电话:13401300028 📱📱📱📱🔣1⃣9⃣🔣2⃣8⃣ 📱📱📱📱每个项目都有小剧情,有开头,高潮,结尾 🥴注意事项: ❶:全场明码标价,无办卡,无套路,不上门 ❷:环境一流,独立卫浴,一次性用具齐全 ❸:不收定金 零门槛 可开餐饮酒店发票 剧情✅放松✅鼻吸✅指滑✅ 胸滑✅漫游✅舌漫✅过水✅ 毒龙✅偷桃✅抚摸✅足推✅ 手推✅胸推✅臀推✅腿夹✅ 📱

1👍1

6 Aug 2026, 07:25 UTC≈1,550 views1 reactionsread 28 August 2026
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😊新北高奢SPA综合实体门店😊 全新装修30间豪华🥰单间🥰配套干湿分离独立卫浴等 🥰新北天花板🤌免费小吃、简餐、饮料、停车🅿️ ⭐五星级环境🥰至尊级体验 ⏰营业时间🕒:12:00-02:00 ✅服务:男士专享高奢SPA💋日式调情 🅾莞式体💦60分钟手🐻屯配合出 原价539电报预约:439 ⭐每日出勤7位蛋蛋后🐇颜艺双全 ✅本店承诺:不办卡 没有隐形消费 给我一次信任👍给您十分满意🥰 🛰️联系方式:13372254606 ✈唯一客服: @BeiGe1a 📍:常州市新北区现代城1期F1层沁安spa养生(原颐和)

👎1

7 May 2026, 14:01 UTC≈6,640 views14 reactionsread 28 August 2026
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😆常州&境 .汤泉🟣⚪️🟣😄 🤗 全裸4️⃣🔠实体店无套路 📱📱📱📱📱📱📱 吸皮过💦 漫游🐍漫 鼻息毒🐲 💅滑🐻推 猴子偷🍑 高山流水 海底捞🌙 蛟龙出海🐲 最后 胸推🐻 臀推🍑 手推👋 ,足推,出货 可亲可摸!上下可摸,黑丝诱惑 原价5️⃣9️⃣9️⃣🌀💲4️⃣9️⃣9️⃣ 60分钟出水不限次数 📱📱📱📱: @jingspa3 📱📱📱📱: @jingspa2 📱📱📱📱: @tangquanspa1 主打私密预约制|限量接待|品质体验 妹妹年纪98~07之间可亲可摸可舔可柔 营业时间:12:00~02:00 😃导航:常州市新北区龙虎塘街道盘龙苑15-3号(境汤泉spa) 🟣: 13222562330

14

11 Apr 2026, 15:20 UTC≈8,330 views14 reactionsread 28 August 2026
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🥰常州极品SPA会所全裸4T店优选🥰 主打高颜值,服务一流。 💵原价:4️⃣9️⃣9️⃣ 💵新店开业活动价 3️⃣6️⃣0️⃣ 服务时间50分钟 双飞特价:第二个6️⃣8️⃣0️⃣一龙二凤双倍快乐 🪙新店开业全场:3️⃣6️⃣0️⃣ 🪙新店开业全场:3️⃣6️⃣0️⃣ 🪙新店开业全场:3️⃣6️⃣0️⃣ 🫕性感风骚🫕 🫕颜值在线🫕 🚗停车方便🚗 服务如下 💓鼻息💓指划💓胸划💓 💓滚水💓漫游💓胸推💓 💓毒龙💓蚂蚁上树💗 💓海底捞月💓高山流水💓 全裸4T服务【手推 胸推 臀推,足推】 50分钟 ✅💯无套路、不办卡、没有任何隐型消费 ✅💯安全💯稳定💯可靠🔔 电报预约🚀 : @PangHuzi0 狼友福利群🚀: https://t.me/hertchangzhou 双向机器人🤖: @panghuzhuanyongbot ✅营业时间

14

4 Apr 2026, 14:17 UTC≈7,560 views8 reactionsread 28 August 2026
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江苏#常州#钟楼 ⭐⭐标准9️⃣5️⃣服务,漫游、指滑、口报👄、过水💧、调情、毒龙🐉、等等,全程裸身服务,专注最优质的🔤🔤🔤顾客至上,服务第一👅👅 课时费:4️⃣😀😀服务40分钟单刺。6️⃣🥰🥰服务60分钟无限刺。 6️⃣6️⃣🥰加倍快乐(双飞) 开课时间:中午12点-凌晨1点 优质导师:2-5位在岗(老师实际信息以当天更新为准)⭐⭐ 👍👍:Xiaozu0918 ✈️✈️:@huaxiansh

8

3 Apr 2026, 13:17 UTC≈6,540 views9 reactionsread 10 August 2026
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常州新北区极品94 5T⚡️SPA 位置:#江苏#常州#新北区 营业时间:12:00-凌晨2:00 服务:🐻推👋推,足推🐬推,毒🐉过水,漫游,吸皮,🐻滑,指滑,猴子偷🍑,高山流水,海底捞🌛,可亲,可摸,可揉,骚话连篇。可69,👅吻,可变装,丝袜情趣可选 😘口秀 首单预约有优惠,品质服务有保障! 预约特价:439/约50分钟 2次 双飞价格:439➕300 优惠套餐价格:439➕30(洗脸,面膜。躺采,情趣制服) 独立卫生间,淋浴 无任何隐形消费 地址:新北区太湖中路 联系方式:@Aa120113 交友群: https://t.me/xinbeispa 频道号:https://t.me/czxinbei

9

Showing the 6 most recent of 6 posts we hold for @xxlmspa. 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

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 30 August 2026 — this entry's latest reading, not the date you are reading this.

“常州⌛黄金门票” (@xxlmspa), 7,372 subscribers as measured 30 August 2026. Telegram Register, tgregister.com/channel/xxlmspa.

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.