Telegram RegisterThe public register of Telegram

Channel

💗 甄乐曦 萧山区开课中 💗

@zhenlexi27

On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Handles named that no longer answer · Cite this entry

12,958subscribers

+75 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-1001927807635
TypeChannel
Username@zhenlexi27
Description个人兼职 双向 @LexiaiaiBot
CreatedBetween 1 April 2023 and 31 October 2023— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live14 August 2026
Measurements held8
Confirmed unchanged1 time, most recently 14 August 2026
On Telegramt.me/zhenlexi27

Growth

12,88312,95812,920.57 August 2026 — 12,883 subscribers8 August 2026 — 12,899 subscribers9 August 2026 — 12,900 subscribers10 August 2026 — 12,902 subscribers11 August 2026 — 12,911 subscribers12 August 2026 — 12,928 subscribers13 August 2026 — 12,940 subscribers14 August 2026 — 12,958 subscribers7 August 202614 August 2026
8 measurements spanning 7 days, net +75. 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 12,872–12,969 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
14 Aug 2026, 23:2612,958+18
13 Aug 2026, 12:2712,940+12
12 Aug 2026, 10:3312,928+17
11 Aug 2026, 08:2312,911+9
10 Aug 2026, 09:3612,902+2
9 Aug 2026, 11:3112,900+1
8 Aug 2026, 13:4612,899+16
7 Aug 2026, 17:4812,883first reading

Engagement

20 posts held, back to 1 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 17 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
30.3%
avg views ÷ 12,958 subscribers
Avg views / post
3,920
1 post measured
Reaction rate
0.332%
reactions ÷ views · ER floor
Posts in window
2
of 20 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 held20 (1 April 202610 August 2026)
Views total3,920
Reactions total13
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken15 Aug 2026, 12:12 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

Photos
16
Videos
4
Links
36

Lifetime counters from Telegram’s own channel header, read 15 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.

Video runtime
23s
Average length
8s

Measured directly from 3 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

205 reactions across 17 posts, in 9 distinct kinds. The most used accounts for 72.7% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
14972.7%
😍2713.2%
🔥104.88%
💯73.41%
❤‍🔥62.93%
🤗31.46%
👍10.488%
😭10.488%
🤩10.488%

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 17 of the 20 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 205reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 20 most recent posts we hold, published 1 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

27 May 2026, 11:11 UTC≈23,900 views30 reactionsread 15 August 2026
Video

合情 合理 合法 和你……..

15😍15

20 May 2026, 15:52 UTC≈20,600 views11 reactionsread 15 August 2026

千遇千寻(上海-杭州)报告模板: https://t.me/shanghaihongding 【妹子花名】:#甄乐曦 【联系方式】:@zhenlexi 【验证留名】:順風順水 【地址】:#萧山 【修车水费】:1600p 【硬件条件】人照相符,身材高挑,皮肤好,课室环境整洁干净 【软件条件】情绪价值很高,进门不紧不慢,主动聊天,增进亲密度,服务三点口,很认真,蛇纹主动,口牛牛是不是深喉,舔蛋蛋,技术一流 【其他补充内容或总结】拿下乐曦ls竞拍,随后约课,因为是520时间比较紧,ls时间观念很强,给每位ly留足1小时,顺利约上,准时到达,ls遥控上楼。进门看到ls人照相符,本人颜值很高,身材高挑,愉快交了水费。Ls也没有急着洗澡,一起坐着聊会天,增进感情,迅速混熟之后,ls放水帮我洗澡,全程帮洗,很认真,洗后擦干进入课室。Ls装备一应俱全,穿上丝袜非常带感,随后让我躺下开始服务。主动蛇纹,很投入,随后舔咪咪,口牛牛都很认真,时不时深

10🤗1

17 May 2026, 05:41 UTC≈15,400 views15 reactionsread 15 August 2026
Photo

以后的要百变风格了,😃……

🔥105

17 May 2026, 02:40 UTC≈15,800 views11 reactionsread 15 August 2026

繁花报告模板:https://t.me/HZFHLYQ 【优势】 【劣势】 【妹子花名】:#甄乐曦 【联系方式】:@zhenlexi 【妹子年龄】:22左右 【验证留名】:张浩 【验证时间】:5月16日 【上课费用】:32pp 【颜值】:人照相似度,9分穿搭/气质/形象如何 【身材】:175左右 看100斤左右 正常肤色,有C有几个纹身 【服务态度】:课表里都可以有 【时间管理】:时间合理,没有罚站也待够满中 【卫生环境】:房间干净整洁 帮洗澡,方便停车 【额外加分项】:腿长,浓眉大眼黑长直发,瘦瘦高高一说一笑、服务态度很好 【综合评价】:超级好评 【流程小文】:提前问了乐曦几次,因为她开课很佛系之约前一天的课、今天终于有时间提前一天约她 付了200定金,期待第二天见面萧山区有点远 小区里很方便不用登记遥控上楼第一次见面眼前一亮,坐在沙发亲亲抱抱,迫不及待去洗澡,帮我洗澡擦身体准备好漱口水、还有很多情趣内衣可以选,上

11

14 May 2026, 04:55 UTC≈12,400 views8 reactionsread 15 August 2026
Photo

萧山区开课中

❤‍🔥61🤩1

29 Apr 2026, 09:24 UTC≈19,600 views11 reactionsread 15 August 2026
Forwarded from @jiuyigongguanrib

沪杭91公馆报告 https://t.me/jiuyigongguann 必填项: 【妹子花名】:#甄乐曦 【联系方式】:@zhenlexi 【验证留名】:大补情郎 【验证时间】:4月9日 【修车水费】:1600p 【流程小文】:之前就看到过好评,尝试约了一下,就没看手机去健身了,快练完了看到老师有空,抢在另一个狼友前付了定(后来老师和我说的还有一个人和我约同一个时间)。练完累累的,开车到老师工作室,是头课,进去看到本人确实浓眉大眼,浓颜系列的,有点像范冰冰,个子很高瘦瘦的。老师挺外向的还和我开玩笑说为啥去健身不把力气留在她身上哈哈。之后就是陪浴帮洗,漱口,主动提供情趣选择,丝袜也都是新的。 调情调得差不多,气氛到了老师就主动大蟒蛇,然后开始口,口活真好,本来以为主打颜值的老师应该技术不咋地,没想到口活属于T1级别,给到一个顶级。平时我对口不是很感冒,因为喜欢身材劲爆的巨乳型最爱的环节是炒菜揉面,但是今天既然来得是颜值型的,那

11

28 Apr 2026, 02:37 UTC≈16,100 views13 reactionsread 15 August 2026

杭州基金会:https://t.me/Foundation_Of_HangZhou 【出击时间】:2026-04-27 【老师花名】:甄乐曦 【出击留名】:Lascy Cuby 【开课位置】:萧山 【修车水费】:1600P 【人照评分】:9.5 【颜值评分】:10 【身材评分】:10 【服务评分】:9.5 【态度评分】:10 【环境评分】:9.5 【综合评分】:9.75 【过程描述】: 好久没 CJ 了,二弟表示强烈抗议🙅,故此周末在榜单 YY 选妃👑,刷到乐曦老师,突然眼神一亮✨。早有耳闻乐曦宝子的神颜加之好兄弟前几天去完后给我极强的好评反馈,果断约课。乐曦老师是自聊,回复较慢,漫长等待时间⏳,总算双勾回复,排好课程,也是让沉寂已久的二弟吃顿大餐🍽。第二天一早和老师确认时间和地点,欣然前往。小区课室,不用登记,停车也方便,乐曦老师遥控上楼,安全意识非常强🔒,一顿爬楼到达课室,开门笑脸相迎😊。高挑的身材配上黑色小吊带绝绝子👗,

12👍1

Showing the 12 most recent of 20 posts we hold for @zhenlexi27. 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 — 839,763 of 1,480,688entries 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.

Forward network

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 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.

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

“💗 甄乐曦 萧山区开课中 💗” (@zhenlexi27), 12,958 subscribers as measured 14 August 2026. Telegram Register, tgregister.com/channel/zhenlexi27.

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.