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Channel
杭州女仆馆在役女仆
@maids_verified
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Posts edited after publishing · Posts recorded as deleted · Citations · Handles named that no longer answer · Cite this entry
32,401subscribers
+5,530 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 31,623–100,000.
Register entry
| Telegram ID | -1002473402480 |
|---|---|
| Type | Channel |
| Username | @maids_verified |
| Created | Between 1 September 2024 and 31 March 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 6 November 2026 |
| Measurements held | 57 |
| Confirmed unchanged | 1 time, most recently 6 November 2026 |
| On Telegram | t.me/maids_verified |
Topic
Other / unclassifiable — 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 9 September 2026 and assigned it the closest of 31 fixed categories, at 66% 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 the other topics.
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 6 Nov 2026, 10:04 | 32,401 | -15 |
| 5 Nov 2026, 10:46 | 32,416 | -6 |
| 4 Nov 2026, 09:39 | 32,422 | -81 |
| 3 Nov 2026, 09:39 | 32,503 | -42 |
| 2 Nov 2026, 12:29 | 32,545 | -9 |
| 1 Nov 2026, 09:36 | 32,554 | -30 |
| 31 Oct 2026, 11:06 | 32,584 | -32 |
| 30 Oct 2026, 10:39 | 32,616 | -50 |
| 29 Oct 2026, 07:41 | 32,666 | -31 |
| 28 Oct 2026, 03:29 | 32,697 | -15 |
| 27 Oct 2026, 02:37 | 32,712 | -13 |
| 26 Oct 2026, 05:48 | 32,725 | -27 |
| 25 Oct 2026, 04:36 | 32,752 | -48 |
| 24 Oct 2026, 01:37 | 32,800 | -214 |
| 23 Oct 2026, 04:36 | 33,014 | -305 |
| 22 Oct 2026, 07:37 | 33,319 | -31 |
| 20 Oct 2026, 23:49 | 33,350 | -15 |
| 19 Oct 2026, 22:34 | 33,365 | +236 |
| 18 Oct 2026, 21:10 | 33,129 | +289 |
| 17 Oct 2026, 19:01 | 32,840 | first reading |
Engagement
336 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 164 pages of Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 1.13%
- avg views ÷ 32,401 subscribers
- Avg views / post
- 366
- 103 posts measured
- Reaction rate
- 0.099%
- reactions ÷ views · ER floor
- Posts in window
- 104
- of 336 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 20 of 103 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 5 November 2026 |
|---|---|
| Posts held | 336 (5 August 2026 – 5 November 2026) |
| Views total | 37,707 |
| Reactions total | 27 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 6 Nov 2026, 09:04 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
- 8m 46s
- Average length
- 13s
Measured directly from 42 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
80 reactions across 44 posts, in 3 distinct kinds. The most used accounts for 92.5% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 74 | 92.5% | |
| 👍 | 5 | 6.25% | |
| 😱 | 1 | 1.25% |
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 56 of the 336 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 80 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 336 most recent posts we hold, published 5 August 2026 to 5 November 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
Telegram’s own ‘edited’ marker: 5 of 104 posts held from the last 30 days (4.81%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).
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👍1
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本群于2026-11-02 12:00至2026-11-02 22:00举行抽奖活动,,可发送“刮刮乐”参与。每人最多可抽奖20次,每次抽奖会消耗萌点40。 奖品如下: 🎁 #萌酱丽莎 @cryptseraph 二免一 └ 已抽0 剩余1 中奖率0.47% 🎁 萌点100 └ 已抽0 剩余5 中奖率2.34% 🎁 萌点40 └ 已抽1 剩余79 中奖率36.92% 🎁 萌点20 └ 已抽1 剩余79 中奖率36.92% 中奖人(2) SebastianCate - 萌点20 - 2026-11-02 13:00:07 九龙街张先生 - 萌点40 - 2026-11-02 12:59:48
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女仆专家 @maides_bot 目前实现了以下功能: 商家发送(休息、满)调整营业状态,并动态展示 群里发送(找*、附近、出击、“地区”、预约xx)查询 用户发送(预约)回复商家或发送(预约xx),通过机器人联系商家 私聊点击(写车评),输入店名或客服用户名,点击相应模块打分,描述过程并提交;已写好测评,直接发送,自助提交 附近:附近十公里内开课的商家 出击:所有已上榜的商家 上城:上城地区已营业的商家 联系XX:通过机器人与xx店联系
👍1
Photo, posted without a caption
Showing the 12 most recent of 336 posts we hold for @maids_verified. 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.
Posts edited after publishing
@maids_verified edited 2 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.
- First edit seen
- 25 October 2026
- Most recent edit
- 3 November 2026
Posts recorded as deleted after publishing
We recorded 13 posts on @maids_verified as deleted — posts this register held that were missing from the channel’s public page on two separate reads, taken from different network addresses at least an hour apart.
A deletion is not wrongdoing. This register can see that a post it held is no longer on the channel’s public page, and when — not why. Expired ad placements, reposts, rotating links and corrections all look the same. This is a count of recorded detections, not an exact total: it misses deletions we could not see, because only a post we held and later re-read inside the page can be seen to go, and it may include a small number of wrong records. How this is measured.
- First seen missing
- 4 September 2026
- Most recent seen missing
- 5 November 2026
- Median time before seen missing
- 25 hours
- Seen missing in the last 30 days
- 8
Forward network
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Republishes
Channels on the register whose posts this channel has forwarded.
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 9 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.
@maid_report · 14,11647 posts小狗诱饵🐶恋爱体验馆🌸
@maoxiaotuan · 7,0823 posts杭州女仆馆新人女仆
@maids_certificate · 19,5542 posts女仆头条日报
@nvputoutiaoribao · 1,0052 posts💖四叶草女仆恋爱馆【防失联】💖
@hangzhousiyecao6 · 4331 post杭州小花园女仆馆频道
@hhl25533 · 5581 post杭州keai恋爱女仆馆
@keaimeishaonv521 · 1,1371 post软糖熊的恋爱小记
@ruantangxing666 · 3981 post杭州桃奈奈测评
@Taonn9 · 671 post
Names
Channels on the register whose handles appear in this channel's posts.
@maid_union · 36,88115 posts杭州女仆馆新人女仆
@maids_certificate · 19,55410 posts杭州小花园女仆交流群
@hhl254202 · 3,9224 posts杭州女仆星悦恋爱体验馆
@asklhfdklsa · 4,7792 posts星星屋陪玩(颜值版)
@bjEverlovenp · 4,8852 posts杭州女仆小酒窝(排班看置顶)
@Changejieyouchat · 9,8042 posts杭州池奈女仆体验馆
@CHINAI_nvpu · 4072 posts❄️糯叽屋❄️的ootd
@hzgs78 · 392 posts❄️糯叽屋❄️测评基地
@hzgs91 · 82 posts秘密
@hznp78911 · 682 posts❄️糯叽屋❄️交流群
@hznp9 · 5412 posts月离女仆频道
@jzmsoxj · 5,9392 posts星悦恋爱女友频道
@kdklaslkjl · 2,1792 posts杭州铃汐女仆馆
@kkcxww · 1,2512 posts杭州铃汐女仆频道
@kkcxwwpin · 3652 posts克拉拉测评群
@KLLcp12 · 3862 posts杭州克拉拉女仆恋爱交流群(余杭)
@KLLJLQ12 · 4,5682 posts杭州克拉拉女仆恋爱馆
@KLLZL12 · 1,9822 posts美好时光女仆——群组
@mhsgqz888 · 5,1032 posts测评
@xingyuecep · 742 posts月离女仆交流群
@xiskxk · 5,8632 posts【极致欢愉】纯享射出spa 🛁
@xnlspaqz · 13,3612 posts杭州女仆测评区(模版在置顶)
@ylnpcpq · 1,2852 posts夜影·女仆桌游群
@yynvpu · 3,6432 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.
Handles this channel named that no longer answer
- Dead references
- 10
- handles named in this channel’s posts, vacant today
- Evidenced gone
- 10
- we ourselves saw one of these resolve, at some point
- Never seen alive
- 0
- vacant every time we have ever looked
@maids_verified named 10 handles 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.
Evidenced gone
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.
named in 2 posts, 5 October 2026 – 6 October 2026 · confirmed gone 14 October 2026 (two independent sightings — see how we confirm a dead handle)evidenced
named in 2 posts, 5 October 2026 – 6 October 2026 · confirmed gone 15 October 2026 (two independent sightings — see how we confirm a dead handle)evidenced
named in 1 post, 18 October 2026 – 18 October 2026 · confirmed gone 24 October 2026 (two independent sightings — see how we confirm a dead handle)evidenced
named in 1 post, 18 October 2026 – 18 October 2026 · confirmed gone 24 October 2026 (two independent sightings — see how we confirm a dead handle)evidenced
named in 1 post, 23 September 2026 – 23 September 2026 · confirmed gone 14 October 2026 (two independent sightings — see how we confirm a dead handle)evidenced
named in 1 post, 23 September 2026 – 23 September 2026 · confirmed gone 14 October 2026 (two independent sightings — see how we confirm a dead handle)evidenced
named in 1 post, 4 September 2026 – 4 September 2026 · confirmed gone 10 October 2026 (two independent sightings — see how we confirm a dead handle)evidenced
named in 1 post, 30 August 2026 – 30 August 2026 · confirmed gone 10 October 2026 (two independent sightings — see how we confirm a dead handle)evidenced
named in 1 post, 30 August 2026 – 30 August 2026 · confirmed gone 12 October 2026 (two independent sightings — see how we confirm a dead handle)evidenced
named in 1 post, 30 August 2026 – 30 August 2026 · confirmed gone 3 November 2026 (two independent sightings — see how we confirm a dead handle)evidenced
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 6 November 2026 — this entry's latest reading, not the date you are reading this.
“杭州女仆馆在役女仆” (@maids_verified), 32,401 subscribers as measured 6 November 2026. Telegram Register, tgregister.com/channel/maids_verified.
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.