💗林若萱💗萧山💗 pinned a photo

Channel
💗林若萱💗萧山💗
@bhkggh
On this record: Topic · Growth · Engagement · Reactions · Posts · Citations · Cite this entry
6,696subscribers
-1,201 since we began measuring on 4 September 2026
Risers and fallers across the register · movement among entries of 3,162–10,000.
Register entry
| Telegram ID | -1002352565343 |
|---|---|
| Type | Channel |
| Username | @bhkggh |
| Created | Between 1 September 2024 and 31 March 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 4 September 2026 |
| Last confirmed live | 6 November 2026 |
| Measurements held | 18 |
| Confirmed unchanged | 1 time, most recently 6 November 2026 |
| On Telegram | t.me/bhkggh |
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 19 September 2026 and assigned it the closest of 31 fixed categories, at 57% 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, 15:15 | 6,696 | -79 |
| 3 Nov 2026, 04:28 | 6,775 | -107 |
| 30 Oct 2026, 22:48 | 6,882 | -166 |
| 28 Oct 2026, 07:00 | 7,048 | +776 |
| 24 Oct 2026, 21:50 | 6,272 | -184 |
| 21 Oct 2026, 17:34 | 6,456 | -88 |
| 18 Oct 2026, 04:49 | 6,544 | -391 |
| 14 Oct 2026, 23:55 | 6,935 | +272 |
| 11 Oct 2026, 23:58 | 6,663 | -29 |
| 5 Oct 2026, 06:36 | 6,692 | +376 |
| 26 Sept 2026, 13:57 | 6,316 | -5,555 |
| 19 Sept 2026, 13:40 | 11,871 | -561 |
| 17 Sept 2026, 02:40 | 12,432 | -741 |
| 15 Sept 2026, 06:01 | 13,173 | +6,237 |
| 11 Sept 2026, 06:16 | 6,936 | -933 |
| 6 Sept 2026, 01:55 | 7,869 | -28 |
| 4 Sept 2026, 12:26 | 7,897 | no change |
| 4 Sept 2026, 12:22 | 7,897 | first reading |
Engagement
45 posts held, back to 14 July 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 7 pages of Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 14.5%
- avg views ÷ 6,696 subscribers
- Avg views / post
- 971
- 23 posts measured
- Reaction rate
- 0.461%
- reactions ÷ views · ER floor
- Posts in window
- 25
- of 45 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.
| Window | Rolling 30 days · latest post in window 6 November 2026 |
|---|---|
| Posts held | 45 (14 July 2026 – 6 November 2026) |
| Views total | 22,331 |
| Reactions total | 103 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 6 Nov 2026, 12:56 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
174 reactions across 39 posts, in 7 distinct kinds. The most used accounts for 75.9% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 132 | 75.9% | |
| 👍 | 24 | 13.8% | |
| 💯 | 6 | 3.45% | |
| 😘 | 5 | 2.87% | |
| 🥰 | 3 | 1.72% | |
| 💋 | 2 | 1.15% | |
| 😍 | 2 | 1.15% |
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 39 of the 45 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 174 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 45 most recent posts we hold, published 14 July 2026 to 6 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: 0 of 25 posts held from the last 30 days (0%) 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
起床啦饱饱 提前预约啦😊
❤2
开课啦饱饱 头课可约哦💃
❤2
起床啦饱饱😊 头课可约啦❤️
❤3🥰2
杭州秋雅总群:https://telegram.me/nanjinggeren66 🌳【客名】:酒不醉 📆【日期】: 11月2日 🧘♀【老师】: #林若萱 📮【联系】:@linruoxuanh 🏡【位置】:萧山区 💰【课费】:500p 🌏【罩杯】:D+ 🧖♀【服务】:莞式 📋【详情】:作为去了N次的老师,若萱现在也是个小满姐,且有成为大满姐的趋势,报告也写了好几篇,这里不再多做赘述,这次从几个方面进行客观陈述,供各位没去过的狼友参考。 1、颜值:夯。不说顶颜,画个淡妆是小美女级别,能符合绝大部分人的审美,(个人理解。因为每个狼友都有自己喜欢的类型) 2、身材:人上人。苗条但不瘦,身高不算高,但是D++的胸又弥补了这一点,是抱在怀里软软的软妹子,贴着胸部尤其舒服。 3、服务:顶级。课表内容都有,不下菜,只要不是素质过低或卫生太差,都会认真服务,比一般嫩妹服务多,很听话,不过…
❤3
宝宝起床啦啦啦💃 可约头课啦啦啦啦💃
❤3😘2
杭州Alex教你123: https://t.me/hzdanai 【老师花名】:#林若萱 【上课费用】:1500包时 【上课区域】:#萧山 【出击评价】:#好评 【出击狼友】: zw hhj 【老师特点】: #情绪价值 #doi体验 【老师车牌】: @linruoxuanh #硬件配置 身高170,体重55kg,年龄97,颜值高,人照一致,身材好,胸D,手感软,无腰部赘肉,,屁股翘,腿细 #服务内容 【陪浴】,【舔胸】,【指划】,【毒龙】,【按摩】,【胸推】,【水中萧】,【事后萧】,【口交】,69 #情绪价值 有亲和力,有女友感,躺在怀里搂着 #态度意识 听话,主动服务,进门递水,面带微笑服务,陪浴后帮擦 #日感反馈 女上,传教士,后入都有。老师的体力好,出水量,屌感好,娇喘,身体颤抖 #精选黄文 特别喜欢大胸,而且看到老师的照片性感诱人就更喜欢了,看到频道里都是好评,立马预约,课室地点正好在我上班附近…
❤4
起床啦饱饱😊 头课可约哦😊
👍4
开课啦饱饱 头课可约啦
💯3👍2
🐴杭州无内鬼报告模板2.0 【位置艺名】:林若萱 【联系方式】: @linruoxuanh 【喝茶留名】: 昨天 【喝茶时间】: 昨天 【喝茶价格】: 包时 【芳龄身高】: 挺高 【罩杯手感】: c手感不错 【服务内容】: 都是按照课表服务挺热情细致,老师是东北大妞性格非常好,完全不冷场,眼睛大大的耐看型,也很温柔,性价比是非常高的,可以冲好兄弟们 【优点缺点】: 【体验细节】: 挺细节的,老师欲望挺大的,差点没给他干服,包时干了四次,每次都很爽,知识什么的都很配合,如果有时候问的话,我愿意多加200 【温馨提醒】:报告仅供参考,请理性选择,切勿对号入座。 👑👑👑无内鬼报告回收计划已启动 ,提交报告得积分1积分等于1软妹币各种白嫖半价好礼等你兑换。提交报告可助力老师入驻免费无内鬼精选榜单~更有机会入围杭州极品必刷榜 无内鬼管理员 @Twittermage 无内鬼 永久域名 @hangzhouwuneigui 任何时间任何地点搜索…
👍4❤1
起床饱饱 提前预约哦💕
❤4😘1
Showing the 12 most recent of 45 posts we hold for @bhkggh. 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.
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 5 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.
Names
Channels on the register whose handles appear in this channel's posts.
@hangzhoubandao520 · 92,6956 posts杭州探花楼
@hz5hz · 54,8303 posts杭州探花楼楼凤认证榜(新)
@ij2222 · 77,7613 posts杭州Alex教你123
@hzdanai · 41,4182 posts杭州秋雅(个人榜)
@nanjinggeren66 · 19,7542 posts若萱的后花园
@ruoxuanhhy · 4,5492 posts杭州无内鬼4.0
@wuneiguiyydds · 36,8352 posts杭州半岛新人工兵频道
@bandaofuli · 46,5111 post杭州茶馆
@hzcg20258 · 17,0091 post杭州无内鬼精选榜单🆕
@hzwmwm · 18,4911 post
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 6 November 2026 — this entry's latest reading, not the date you are reading this.
“💗林若萱💗萧山💗” (@bhkggh), 6,696 subscribers as measured 6 November 2026. Telegram Register, tgregister.com/channel/bhkggh.
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.