11.7号出勤 点击蓝色名字直达老师照片及测评 出勤: 香香 由美 依依 多多 欢欢 恋恋 菲菲 沫沫 待更新 聊天记录不用删 累计满五次可以送一个半价 《半价除外》不想留记录可以仅删除自己
Signed 情调丝足13662155773

Channel
@qingdiaosizu020
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
7,543subscribers
+3,304 since we began measuring on 8 August 2026
Risers and fallers across the register · movement among entries of 3,162–10,000.
| Telegram ID | -1003202491668 |
|---|---|
| Type | Channel |
| Username | @qingdiaosizu020 |
| Created | Between 1 October 2025 and 31 January 2026 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 8 August 2026 |
| Last confirmed live | 7 November 2026 |
| Measurements held | 25 |
| Confirmed unchanged | 1 time, most recently 7 November 2026 |
| On Telegram | t.me/qingdiaosizu020 |
Adult — 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 13 September 2026 and assigned it the closest of 31 fixed categories, at 62% 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.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 7 Nov 2026, 10:35 | 7,543 | +84 |
| 4 Nov 2026, 18:36 | 7,459 | +89 |
| 1 Nov 2026, 15:51 | 7,370 | +159 |
| 29 Oct 2026, 12:31 | 7,211 | +51 |
| 26 Oct 2026, 21:28 | 7,160 | +59 |
| 24 Oct 2026, 05:20 | 7,101 | +142 |
| 21 Oct 2026, 07:34 | 6,959 | +123 |
| 18 Oct 2026, 08:26 | 6,836 | +123 |
| 15 Oct 2026, 15:19 | 6,713 | +140 |
| 13 Oct 2026, 00:19 | 6,573 | +284 |
| 6 Oct 2026, 13:36 | 6,289 | +298 |
| 29 Sept 2026, 12:40 | 5,991 | +396 |
| 16 Sept 2026, 02:18 | 5,595 | +59 |
| 11 Sept 2026, 22:20 | 5,536 | +169 |
| 7 Sept 2026, 06:36 | 5,367 | +76 |
| 2 Sept 2026, 23:14 | 5,291 | +83 |
| 31 Aug 2026, 00:57 | 5,208 | +147 |
| 27 Aug 2026, 16:15 | 5,061 | +79 |
| 24 Aug 2026, 23:18 | 4,982 | +176 |
| 21 Aug 2026, 00:22 | 4,806 | first reading |
25 posts held, back to 14 June 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 12 pages of Telegram’s post history, 20 posts per page.
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 12 of 13 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 7 November 2026 |
|---|---|
| Posts held | 25 (14 June 2026 – 7 November 2026) |
| Views total | 51,709 |
| Reactions total | 52 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 7 Nov 2026, 05:25 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.
Measured directly from 8 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.
128 reactions across 22 posts, in 4 distinct kinds. The most used accounts for 96.9% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 124 | 96.9% | |
| 👍 | 2 | 1.56% | |
| 👎 | 1 | 0.781% | |
| 😁 | 1 | 0.781% |
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 23 of the 25 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 128 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 25 most recent posts we hold, published 14 June 2026 to 7 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.
Telegram’s own ‘edited’ marker: 9 of 13 posts held from the last 30 days (69.2%) 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).
11.7号出勤 点击蓝色名字直达老师照片及测评 出勤: 香香 由美 依依 多多 欢欢 恋恋 菲菲 沫沫 待更新 聊天记录不用删 累计满五次可以送一个半价 《半价除外》不想留记录可以仅删除自己
Signed 情调丝足13662155773
11.6号出勤 点击蓝色名字直达老师照片及测评 出勤: 由美 依依 多多 米拉 欢欢 恋恋 菲菲 沫沫 聊天记录不用删 累计满五次可以送一个半价 《半价除外》不想留记录可以仅删除自己 预约客服⭐️ @qingdiaosizu02 双向客服⭐️ @QDSZ99_bot 福利视频⭐️ @qingdiaosizu999 课表请看置顶
Signed 情调丝足13662155773
天津天花板•情调丝足⭐⭐ 依依 04年 𝐇𝐢𝐠𝐡𝐭/165cm 𝐖𝐞𝐢𝐠𝐡𝐭/44kg 𝐁𝐮𝐬𝐭/C 依依 身高165 体重98 胸围C 真实测评01
❤3
Signed 情调丝足13662155773
天津天花板•情调丝足⭐⭐ 水水 01年 𝐇𝐢𝐠𝐡𝐭/165cm 𝐖𝐞𝐢𝐠𝐡𝐭/44kg 𝐁𝐮𝐬𝐭/B 水水 身高165 体重88 胸围B
❤2
Signed 情调丝足13662155773
天津天花板•情调丝足⭐⭐ 欢欢 06年 𝐇𝐢𝐠𝐡𝐭/163cm 𝐖𝐞𝐢𝐠𝐡𝐭/43kg 𝐁𝐮𝐬𝐭/B 欢欢 身高163 体重86 胸围B 真实测评01
❤3
Signed 情调丝足13662155773
天津天花板•情调丝足⭐⭐ 菲菲 03年 𝐇𝐢𝐠𝐡𝐭/165cm 𝐖𝐞𝐢𝐠𝐡𝐭/53kg 𝐁𝐮𝐬𝐭/C 菲菲 身高165 体重106 胸围C 真实测评01 真实测评02 真实测评03 真实测评04 真实测评05 真实测评06 真实测评07 真实测评08
❤8
Signed 情调丝足13662155773
天津天花板•情调丝足⭐⭐ 由美 03年 𝐇𝐢𝐠𝐡𝐭/165cm 𝐖𝐞𝐢𝐠𝐡𝐭/43kg 𝐁𝐮𝐬𝐭/B 由美 身高165 体重86 胸围B 真实测评01
❤5
Signed 情调丝足13662155773
天津天花板•情调丝足⭐⭐ 恋恋 02年 𝐇𝐢𝐠𝐡𝐭/170cm 𝐖𝐞𝐢𝐠𝐡𝐭/44kg 𝐁𝐮𝐬𝐭/C 恋恋 身高170 体重88 胸围C 真实测评01 真实测评02 真实测评03 真实测评04
❤6
Signed 情调丝足13662155773
新店多了一个套餐二 但是11.1号才能上线 最近会陆续培训 兄弟们有什么好的想法可以留言 尽可能都会加上 https://t.me/qingdiaosizu020/26
❤3
Signed 情调丝足13662155773
本店导航大概位置:彩云间艺术培训学校 (避免到了找不着 请导航这个的具体位置 到了会发您一个导向图很好找)
❤2👎1
Signed 情调丝足13662155773
情调家丝足玩法介绍🤭: 介绍:作为一名丝足爱好者,从小就对穿丝袜女性有憧憬的向往,想摸腿,想舔脚,想闻原味、想XX,故在柔式基础上增加丝足的环节,增加与丝袜美腿美脚的互动,特开此店,与共同爱好者一起交流学习。 现将本人的心得、本店的玩法分享给各位狼友: 1.怎么玩: 首先要了解咱们家的服务内容是柔式手法➕丝足服务,服务前可以跟老师提前沟通出水次数,服务过程中也可以根据自己的敏感点,让老师选择用手、腿、脚、🐻等方式出水;出水后也可以根据剩余时间和自己的情况,跟老师沟通可以再按会摩(老师们都会专业按摩)、聊会天都可以的,老师们不会在服务时间未结束催客户。 2.玩法心得 首先课表上的内容,老师们会做到位,做好;其次,兄弟们花了钱,出来玩,就是为了满足自己的一些小癖好,得到情绪价值,不要不好意思说,所以有一些不过分的小癖好都可以跟老师直接沟通,只要老师接受都可以去玩(但是课表外的内容…
❤10
Signed 情调丝足13662155773
天津天花板•情调丝足⭐⭐ 柠檬 01年 𝐇𝐢𝐠𝐡𝐭/170cm 𝐖𝐞𝐢𝐠𝐡𝐭/52kg 𝐁𝐮𝐬𝐭/B 柠檬 身高170 体重102 胸围b 真实测评01 真实测评02
❤2
Signed 情调丝足13662155773
Showing the 12 most recent of 25 posts we hold for @qingdiaosizu020. 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.
@qingdiaosizu020 edited 3 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.
We recorded 3 posts on @qingdiaosizu020 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.
Named by 3 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.
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.
@qingdiaosizu020 named 1 handle 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.
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.
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 7 November 2026 — this entry's latest reading, not the date you are reading this.
“天津情调丝足半裸spa” (@qingdiaosizu020), 7,543 subscribers as measured 7 November 2026. Telegram Register, tgregister.com/channel/qingdiaosizu020.
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.