Telegram RegisterThe public register of Telegram

Channel

龙华&松山湖❤️修车资源

@lhhche

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

8,524subscribers

-106 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-1001395708234
TypeChannel
Username@lhhche
Description上榜联系: @CN3456 私聊不了联系双向机器人: @CN6789BOT 深圳修车资源榜 https://t.me/LM8969 深圳学生会 https://t.me/SZXSH8 一键快速进深圳所有群 https://t.me/addlist/jxLTSzufnjIwNDE1
CreatedBetween 1 April 2018 and 30 June 2021— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live11 August 2026
Measurements held3
Confirmed unchanged1 time, most recently 11 August 2026
On Telegramt.me/lhhche

Growth

8,5248,6308,5777 August 2026 — 8,630 subscribers8 August 2026 — 8,621 subscribers11 August 2026 — 8,524 subscribers7 August 202611 August 2026
3 measurements spanning 4 days, net -106. 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 8,508–8,646 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
11 Aug 2026, 05:038,524-97
8 Aug 2026, 11:228,621-9
7 Aug 2026, 16:468,630first reading

Engagement

6 posts held, back to 24 July 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 13 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
1.05%
avg views ÷ 8,524 subscribers
Avg views / post
89.6
5 posts measured
Reaction rate
0.862%
reactions ÷ views · ER floor
Posts in window
6
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. It is computed over the 2 of 5 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 12 August 2026
Posts held6 (24 July 202612 August 2026)
Views total448
Reactions total2
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken12 Aug 2026, 16:16 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

Photos
274
Videos
8
Links
46

Lifetime counters from Telegram’s own channel header, read 12 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
9s
Average length
9s

Measured directly from 1 video 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

2 reactions across 2 posts, in 1 kind.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
2100.0%

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 2 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 2reactions 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 24 July 2026 to 12 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

12 Aug 2026, 06:39 UTC8 viewsread 12 August 2026
Photo

🧩榜单番号 0812-3366 【深圳 惠州 东莞 佛山 广州】95-96均有分店 海选模式 莞式服务 至尊享受 深圳九四丝足水会频道 https://t.me/SzSwK1295/7505 私密莞式 更有多位 学生妹 持续出勤 尊重每位客户,提供个性化服务 顶尖颜值 专业服务 根据需求可定制专属的个性服务,更多姿势服务待哥哥发掘 时间不到服务不停 可加钟可双飞 主打颜值 服务 环境 安全为一体的高端私密男士会所 合作会所每天都有补充颜值高、活好的年轻技师 机器人:@dsfsdsabot QQ在线客服:3809275809 在线客服:@qgsnkyd5_6 深圳区#95-#96频道地址 https://t.me/szgz949596/82 更多: 🌎深圳修车资源导航 资源群:🍀深圳学生会 一键快速进深圳所有群 🔍更多资源福利 👉点我永不失联

8 Aug 2026, 06:05 UTC55 views1 reactionsread 12 August 2026
Photo

🧩榜单番号 112-3199994 #95口爆(海选 会所)😂😀😀😀 📱📱📱📱口爆SPA会所覆盖全深圳区(无套口出)📱📱📱📱 🐨#罗湖 🐨#福田 🐨#宝安 🐨#龙岗 🐨#南山🐨 #龙华 数30+位妹妹上班,御姐,巨乳,萝莉,小骚货各种类型都有,配合度高,主动开放热情,到点海选不满意可换到满意为止听话乖巧 😛套餐:预约价538-598(全裸口一次)60分钟 😝套餐:预约价568-658(全裸口一手一)70分钟 😜套餐:预约价800-888(全裸魔棒口2次)80分钟 🤪套餐:预约价 1000-1180(双飞或加钟全裸口出2次) 😀😀😀😀组团优惠更多( 30-150 ) 😀😀😀😀 📱📱#94丝足(主打00后嫩妹)📱📱 😀😀丝足会所覆盖全深圳区域 😀😀 😀😀😀😀服务内容😀😀😀😀 🐻🐻前段【20分钟】:特色变装躺采,头疗放松,十指弹琴,舌尖漫游,蛇绕全身,耳语调情 🐻🐻中段【30分钟

1

7 Aug 2026, 06:06 UTC70 viewsread 12 August 2026
Photo

🧩榜单番号 0807-3366 深圳全区94-95-96-98会所SAP #龙华 #罗湖 #宝安 #福田 #南山 #龙岗 #光明 #盐田 #坪山 #南山 #95-96口爆《金牌🥇会所》 95价格:568-598各区价格不同 96价格:788-850各区价格不同 #94全区精品店 60分钟 帝王视角任君摆弄姿势 妹妹听话懂配合 价格399-499各地区价格不同 预约QQ:2754796170(QQ不聊项目,只发位置,报预约号) 双向: @szjfnj0bot 私聊: @wwff9495 频道: https://t.me/fvjbvv7 更多: 🌎深圳修车资源导航 资源群:🍀深圳学生会 一键快速进深圳所有群 🔍更多资源福利 👉点我永不失联

31 Jul 2026, 06:53 UTC138 viewsread 12 August 2026
Photo

🧩榜单番号 112-3199994 #95口爆(海选 会所)😂😀😀😀 📱📱📱📱口爆SPA会所覆盖全深圳区(无套口出)📱📱📱📱 🐨#罗湖 🐨#福田 🐨#宝安 🐨#龙岗 🐨#南山🐨 #龙华 数30+位妹妹上班,御姐,巨乳,萝莉,小骚货各种类型都有,配合度高,主动开放热情,到点海选不满意可换到满意为止听话乖巧 😛套餐:预约价538-598(全裸口一次)60分钟 😝套餐:预约价568-658(全裸口一手一)70分钟 😜套餐:预约价800-888(全裸魔棒口2次)80分钟 🤪套餐:预约价 1000-1180(双飞或加钟全裸口出2次) 😀😀😀😀组团优惠更多( 30-150 ) 😀😀😀😀 📱📱#94丝足(主打00后嫩妹)📱📱 😀😀丝足会所覆盖全深圳区域 😀😀 😀😀😀😀服务内容😀😀😀😀 🐻🐻前段【20分钟】:特色变装躺采,头疗放松,十指弹琴,舌尖漫游,蛇绕全身,耳语调情 🐻🐻中段【30分钟

24 Jul 2026, 05:59 UTC177 views1 reactionsread 8 August 2026
Photo

🧩榜单番号 112-3199994 #95口爆(海选 会所)😂😀😀😀 📱📱📱📱口爆SPA会所覆盖全深圳区(无套口出)📱📱📱📱 🐨#罗湖 🐨#福田 🐨#宝安 🐨#龙岗 🐨#南山🐨 #龙华 数30+位妹妹上班,御姐,巨乳,萝莉,小骚货各种类型都有,配合度高,主动开放热情,到点海选不满意可换到满意为止听话乖巧 😛套餐:预约价538-598(全裸口一次)60分钟 😝套餐:预约价568-658(全裸口一手一)70分钟 😜套餐:预约价800-888(全裸魔棒口2次)80分钟 🤪套餐:预约价 1000-1180(双飞或加钟全裸口出2次) 😀😀😀😀组团优惠更多( 30-150 ) 😀😀😀😀 📱📱#94丝足(主打00后嫩妹)📱📱 😀😀丝足会所覆盖全深圳区域 😀😀 😀😀😀😀服务内容😀😀😀😀 🐻🐻前段【20分钟】:特色变装躺采,头疗放松,十指弹琴,舌尖漫游,蛇绕全身,耳语调情 🐻🐻中段【30分钟

1

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

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

“龙华&松山湖❤️修车资源” (@lhhche), 8,524 subscribers as measured 11 August 2026. Telegram Register, tgregister.com/channel/lhhche.

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.