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Channel

白云首家温泉97水汇【情趣制服】

@byjqsh

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

11,283subscribers

-302 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-1003149473145
TypeChannel
Username@byjqsh
CreatedBetween 1 September 2025 and 30 November 2025— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live30 August 2026
Measurements held21
Confirmed unchanged1 time, most recently 30 August 2026
On Telegramt.me/byjqsh

Growth

11,27411,58611,4307 August 2026 — 11,585 subscribers8 August 2026 — 11,586 subscribers10 August 2026 — 11,571 subscribers11 August 2026 — 11,563 subscribers12 August 2026 — 11,557 subscribers13 August 2026 — 11,526 subscribers14 August 2026 — 11,493 subscribers16 August 2026 — 11,488 subscribers17 August 2026 — 11,468 subscribers18 August 2026 — 11,385 subscribers19 August 2026 — 11,298 subscribers20 August 2026 — 11,299 subscribers21 August 2026 — 11,305 subscribers22 August 2026 — 11,309 subscribers24 August 2026 — 11,310 subscribers25 August 2026 — 11,282 subscribers26 August 2026 — 11,274 subscribers27 August 2026 — 11,275 subscribers28 August 2026 — 11,279 subscribers29 August 2026 — 11,288 subscribers30 August 2026 — 11,283 subscribers11,2837 August 202630 August 2026
21 measurements spanning 23 days, net -302. 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 11,227–11,633 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 21
Measured (UTC)SubscribersChange
30 Aug 2026, 10:4811,283-5
29 Aug 2026, 12:2311,288+9
28 Aug 2026, 11:5311,279+4
27 Aug 2026, 12:4711,275+1
26 Aug 2026, 11:3311,274-8
25 Aug 2026, 13:1211,282-28
24 Aug 2026, 14:0411,310+1
22 Aug 2026, 23:5911,309+4
21 Aug 2026, 12:1311,305+6
20 Aug 2026, 15:0211,299+1
19 Aug 2026, 14:3411,298-87
18 Aug 2026, 14:1811,385-83
17 Aug 2026, 14:0811,468-20
16 Aug 2026, 07:0711,488-5
14 Aug 2026, 15:1411,493-33
13 Aug 2026, 07:0411,526-31
12 Aug 2026, 08:4311,557-6
11 Aug 2026, 05:4411,563-8
10 Aug 2026, 03:3011,571-15
8 Aug 2026, 02:2011,586first reading

Engagement

68 posts held, back to 7 August 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 38 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
1.10%
avg views ÷ 11,283 subscribers
Avg views / post
124
66 posts measured
Reaction rate
0.251%
reactions ÷ views · ER floor
Posts in window
68
of 68 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 7 of 66 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 29 August 2026
Posts held68 (7 August 202629 August 2026)
Views total8,158
Reactions total4
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken29 Aug 2026, 10:18 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.

Reaction mix

4 reactions across 4 posts, in 1 kind.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
4100.0%

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 7 of the 68 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 4reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 68 most recent posts we hold, published 7 August 2026 to 29 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

29 Aug 2026, 06:25 UTC51 viewsread 29 August 2026

😁😆🥹 🥰广州白云首家温泉泡澡水汇 金海湾国际97会所(情趣制服换装) 🥰 #白云区 #新市 #三元里 #金沙洲 #水汇 #制服 #丝袜 #97场 #口吹 #磨棒 #毒龙 🫠🫠🫠 🫠 🫠🫠🫠 特色优点:白云首家温泉泡澡97水汇,白云首家温泉度假主题房水疗中心,白云唯一一家支持情趣换装97玩法,主打角色扮演97,技师拥有很多套制服,例如学生装、护士装、OL秘书扮演等等特色情趣玩法,超级稀有的服务,冰火两重天、磨棒、足交是本店的招牌,超大的温泉泡澡池,按摩房空间超级大,2米大床,金海湾国际在白云非常出名,今天终于正式对外开放。店里每天70多位高颜值技师上班,S牌都是极品中的极品,都是从事空姐、秘书、医美、ktv这些行业高薪招聘回来的。白云能有温泉泡澡池的少之又少,本店环境高档,独栋大型水汇,技师超高颜值,服务超顶级,高端天然温泉泡澡池♨️ 全程 #90分钟 时间不到服务不停📃📜

28 Aug 2026, 14:02 UTC152 viewsread 29 August 2026

😁😆🥹 🥰广州白云首家温泉泡澡水汇 金海湾国际97会所(情趣制服换装) 🥰 #白云区 #新市 #三元里 #金沙洲 #水汇 #制服 #丝袜 #97场 #口吹 #磨棒 #毒龙 🫠🫠🫠 🫠 🫠🫠🫠 特色优点:白云首家温泉泡澡97水汇,白云首家温泉度假主题房水疗中心,白云唯一一家支持情趣换装97玩法,主打角色扮演97,技师拥有很多套制服,例如学生装、护士装、OL秘书扮演等等特色情趣玩法,超级稀有的服务,冰火两重天、磨棒、足交是本店的招牌,超大的温泉泡澡池,按摩房空间超级大,2米大床,金海湾国际在白云非常出名,今天终于正式对外开放。店里每天70多位高颜值技师上班,S牌都是极品中的极品,都是从事空姐、秘书、医美、ktv这些行业高薪招聘回来的。白云能有温泉泡澡池的少之又少,本店环境高档,独栋大型水汇,技师超高颜值,服务超顶级,高端天然温泉泡澡池♨️ 全程 #90分钟 时间不到服务不停📃📜

28 Aug 2026, 08:29 UTC107 viewsread 28 August 2026

😁😆🥹 🥰广州白云首家温泉泡澡水汇 金海湾国际97会所(情趣制服换装) 🥰 #白云区 #新市 #三元里 #金沙洲 #水汇 #制服 #丝袜 #97场 #口吹 #磨棒 #毒龙 🫠🫠🫠 🫠 🫠🫠🫠 特色优点:白云首家温泉泡澡97水汇,白云首家温泉度假主题房水疗中心,白云唯一一家支持情趣换装97玩法,主打角色扮演97,技师拥有很多套制服,例如学生装、护士装、OL秘书扮演等等特色情趣玩法,超级稀有的服务,冰火两重天、磨棒、足交是本店的招牌,超大的温泉泡澡池,按摩房空间超级大,2米大床,金海湾国际在白云非常出名,今天终于正式对外开放。店里每天70多位高颜值技师上班,S牌都是极品中的极品,都是从事空姐、秘书、医美、ktv这些行业高薪招聘回来的。白云能有温泉泡澡池的少之又少,本店环境高档,独栋大型水汇,技师超高颜值,服务超顶级,高端天然温泉泡澡池♨️ 全程 #90分钟 时间不到服务不停📃📜

26 Aug 2026, 06:55 UTC216 views0 reactionsread 28 August 2026

😁😆🥹 🥰广州白云首家温泉泡澡水汇 金海湾国际97会所(情趣制服换装) 🥰 #白云区 #新市 #三元里 #金沙洲 #水汇 #制服 #丝袜 #97场 #口吹 #磨棒 #毒龙 🫠🫠🫠 🫠 🫠🫠🫠 特色优点:白云首家温泉泡澡97水汇,白云首家温泉度假主题房水疗中心,白云唯一一家支持情趣换装97玩法,主打角色扮演97,技师拥有很多套制服,例如学生装、护士装、OL秘书扮演等等特色情趣玩法,超级稀有的服务,冰火两重天、磨棒、足交是本店的招牌,超大的温泉泡澡池,按摩房空间超级大,2米大床,金海湾国际在白云非常出名,今天终于正式对外开放。店里每天70多位高颜值技师上班,S牌都是极品中的极品,都是从事空姐、秘书、医美、ktv这些行业高薪招聘回来的。白云能有温泉泡澡池的少之又少,本店环境高档,独栋大型水汇,技师超高颜值,服务超顶级,高端天然温泉泡澡池♨️ 全程 #90分钟 时间不到服务不停📃📜

25 Aug 2026, 06:56 UTC196 viewsread 27 August 2026

😁😆🥹 🥰广州白云首家温泉泡澡水汇 金海湾国际97会所(情趣制服换装) 🥰 #白云区 #新市 #三元里 #金沙洲 #水汇 #制服 #丝袜 #97场 #口吹 #磨棒 #毒龙 🫠🫠🫠 🫠 🫠🫠🫠 特色优点:白云首家温泉泡澡97水汇,白云首家温泉度假主题房水疗中心,白云唯一一家支持情趣换装97玩法,主打角色扮演97,技师拥有很多套制服,例如学生装、护士装、OL秘书扮演等等特色情趣玩法,超级稀有的服务,冰火两重天、磨棒、足交是本店的招牌,超大的温泉泡澡池,按摩房空间超级大,2米大床,金海湾国际在白云非常出名,今天终于正式对外开放。店里每天70多位高颜值技师上班,S牌都是极品中的极品,都是从事空姐、秘书、医美、ktv这些行业高薪招聘回来的。白云能有温泉泡澡池的少之又少,本店环境高档,独栋大型水汇,技师超高颜值,服务超顶级,高端天然温泉泡澡池♨️ 全程 #90分钟 时间不到服务不停📃📜

24 Aug 2026, 13:26 UTC143 viewsread 26 August 2026

😁😆🥹 🥰广州白云首家温泉泡澡水汇 金海湾国际97会所(情趣制服换装) 🥰 #白云区 #新市 #三元里 #金沙洲 #水汇 #制服 #丝袜 #97场 #口吹 #磨棒 #毒龙 🫠🫠🫠 🫠 🫠🫠🫠 特色优点:白云首家温泉泡澡97水汇,白云首家温泉度假主题房水疗中心,白云唯一一家支持情趣换装97玩法,主打角色扮演97,技师拥有很多套制服,例如学生装、护士装、OL秘书扮演等等特色情趣玩法,超级稀有的服务,冰火两重天、磨棒、足交是本店的招牌,超大的温泉泡澡池,按摩房空间超级大,2米大床,金海湾国际在白云非常出名,今天终于正式对外开放。店里每天70多位高颜值技师上班,S牌都是极品中的极品,都是从事空姐、秘书、医美、ktv这些行业高薪招聘回来的。白云能有温泉泡澡池的少之又少,本店环境高档,独栋大型水汇,技师超高颜值,服务超顶级,高端天然温泉泡澡池♨️ 全程 #90分钟 时间不到服务不停📃📜

Showing the 12 most recent of 68 posts we hold for @byjqsh. 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.

Citation-graph rank

Citation-graph rank — 1,329,162 of 1,627,445entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.

Mentions

Named by 1 registered channel — 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 30 August 2026 — this entry's latest reading, not the date you are reading this.

“白云首家温泉97水汇【情趣制服】” (@byjqsh), 11,283 subscribers as measured 30 August 2026. Telegram Register, tgregister.com/channel/byjqsh.

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.