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Channel

脸部护理_秦若瑄

@qrxpyq1

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

1,757subscribers

+666 since we began measuring on 12 September 2026

Risers and fallers across the register · movement among entries of 1,000–3,162.

Register entry

Telegram ID-1004483062434
TypeChannel
Username@qrxpyq1
CreatedBetween 1 June 2026 and 12 August 2026 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded12 September 2026
Last confirmed live17 September 2026
Measurements held3
Confirmed unchanged1 time, most recently 17 September 2026
On Telegramt.me/qrxpyq1

Growth

1,0911,7571,42412 September 2026 — 1,091 subscribers13 September 2026 — 1,407 subscribers17 September 2026 — 1,757 subscribers12 September 202617 September 2026
3 measurements spanning 5 days, net +666. 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 991–1,857 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
17 Sept 2026, 10:581,757+350
13 Sept 2026, 18:381,407+316
12 Sept 2026, 12:221,091first reading

Engagement

15 posts held, back to 12 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 1 page of Telegram’s post history, 20 posts per page.

ERR · 30 days
50.0%
avg views ÷ 1,757 subscribers
Avg views / post
878
7 posts measured
Reaction rate
0.113%
reactions ÷ views · ER floor
Posts in window
8
of 15 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 3 of 7 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 September 2026
Posts held15 (12 August 202612 September 2026)
Views total6,149
Reactions total3
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken12 Sept 2026, 12:22 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
39s
Average length
20s

Measured directly from 2 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

6 reactions across 6 posts, in 1 kind.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
6100.0%

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 6 of the 15 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 6 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 15 most recent posts we hold, published 12 August 2026 to 12 September 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 Sept 2026, 05:47 UTC703 views1 reactionsread 12 September 2026
Photo

🎰 俱乐部 & 秦若瑄 @qinruoxuan 九月福利第二弹 📮 参与条件: 🌏️ 归属地 四川 🪪 必须设置用户名 🎫 加入-脸部护理_秦若瑄 🎫 加入-成都楼凤修车•言师日记 🎫 加入-神秘的出击流水账纪实 🎫 加入-༺ཌༀ成都修车俱乐部ༀད༻ └ 🔑 发送口令﹝脸部护理跟私密爱爱就找秦若瑄﹞ ❗ 口令提示: 请先参与抽奖,再发送口令激活 🎁 奖品内容: 💰️ 50元口令红包 × 2 💰️ 单P半价优惠券 × 2 💰️ 单P白嫖 × 1 💰️ 通用100元优惠券 × 3 ⚠️ 抽奖说明: 1.本次优惠券不可折现,优惠券兑奖有效期为开奖后7天内,逾期作废! 2.口令红包兑换有效期为开奖后48小时内,逾期作废! 3.因炸号,退群,注销账号等原因,超时未兑换等原因的,不予兑奖! 4.中途退群退频道,乱水群都会取消中奖资格! 5.口令已经优惠券找秦若瑄宝宝 @qinruoxuan 🔋 人品加成:⚡️× 9

1

1 Sept 2026, 15:29 UTC≈1,140 views1 reactionsread 12 September 2026

🌸【成都滴滴修车群】 🌸 专用报告 🌸基础信息🌸 【妹子花名】:#秦若瑄 【妹子车牌】:@qinruoxuan 【验证留名】:忘川 【验证时间】:9.1 【所在位置】:昭觉寺 【修车水费】:6P 【是否代聊】:代聊 🌸硬件评价🌸 【身高体重】:身高163 体重49kg 无纹身 皮肤手感光滑 【妹子年龄】:28 【湿度紧度昆感】:老师的户型馒头型一线天/颜色外褐内粉,高等湿度/中等紧度,周围中等毛量 【颜值相似】:人照相似程度9,颜值好看,气质/穿搭时尚 【凶器罩杯】:胸型大小C,乳头颜色褐红色/黄豆大小,胸部手感柔软 🌸软件评价🌸 【环境卫生】:交通/出入方便,房间整洁干净 【服务内容】:鸳鸯浴,A面,舌吻,69,口,丝袜制服,爱爱 【机车行为】:无久等 态度温柔 不玩手机 不催 开课时间宽松 🌸综合评价🌸 【优点缺点】:颜值符合大众标准,长发,大长腿。主动大蟒蛇非常巴适,小家碧玉型,反

1

30 Aug 2026, 01:48 UTC≈1,110 viewsread 12 September 2026

🔥🔥🔥各位帅哥些,从9月1号到15号,写报告减1哦,‼️

27 Aug 2026, 04:39 UTC811 views1 reactionsread 12 September 2026

今日活动 ,前三位送88洗脸项目🌹🌹🌹

1

20 Aug 2026, 15:00 UTC≈1,230 views1 reactionsread 12 September 2026

【成都91修车学院】®专属报告 🔴基础信息 【妹子花名】:#秦若瑄 【妹子车牌】:@qinruoxuan 【验证留名】:三哥 【验证时间】:8月 【所在位置】:昭觉寺 【修车水费】:6P 10PP 【是否代聊】:代聊 🟡硬件评价 【身高体重】:身高163左右,体重95左右,全身干净无纹身,皮肤白滑,冷白皮,手感佳 【妹子年龄】:28 【湿度紧度昆感】:一线天户型,人工白虎,外褐内粉,紧,水多 【人照评分】:9分 【颜值评分】:颜值中上,穿搭性感精致 【凶器罩杯】:天然小c凶圆润饱满,乳头乳晕不大,颜色浅,咪咪敏感,手感佳 🟢软件评价 【环境卫生】:交通出入方便,房间整洁干净 【服务内容】:陪洗,舔凶舔蛋,大蟒蛇,69,凶推,舒适口活,菜单上的都有 【机车行为】:无 🟣综合评价 【优点缺点】:优点颜值冷白皮御姐,爱说爱笑,身材苗条匀称,皮肤白滑,兼职,没啥风尘味,紧,水多,人工白虎,情绪价值高,大蟒蛇

1

20 Aug 2026, 09:53 UTC≈1,070 views1 reactionsread 12 September 2026

【编号】ML1635 【花名】秦若瑄 【车牌】@qinruoxuan 【地址】成华区 【价格】P 600 元 / PP 1000 元 【标签】69 600 代聊 熟女 情绪价值 大蟒蛇 深喉 【颜值】8 分 【身材】8 分 【环境】8 分 【服务】9 分 【经过】头一天遇到检查没有出击成功,第二天约的下午两点,准时抵达,见到老师,人照8.5,熟女御姐类型,本人比较有礼貌、健谈,聊了会天就有了感觉,抱着就是大蟒蛇,吃胸,摸屁股,胸部和臀部柔软有弹性,整个全程可以大蟒蛇,吃鸡可以深喉,口技了得,嫩逼一线天,人工白虎,水超多,69逼里全是水,互动性强,做爱配合,日感棒,换了几个姿势出水,最后意想不到给我来了个回龙萧,那感觉沁人心脾。 ━━━━━━━━ 更多真实测评 · 上百位老师在线 · 打开小程序随时约 → 查看完整资料 / 立即预约(小程序) → 打开小程序看更多老师

1

16 Aug 2026, 05:46 UTC≈1,140 viewsread 12 September 2026
Photo

老公们 😘今天在预约滴滴 🌹🌹🌹

Showing the 12 most recent of 15 posts we hold for @qrxpyq1. 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

Named by 2 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.

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 17 September 2026 — this entry's latest reading, not the date you are reading this.

“脸部护理_秦若瑄” (@qrxpyq1), 1,757 subscribers as measured 17 September 2026. Telegram Register, tgregister.com/channel/qrxpyq1.

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.