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Channel

黛玉的小窝

@daiyudexiaowo

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

3,265subscribers

+388 since we began measuring on 3 September 2026

Risers and fallers across the register · movement among entries of 3,162–10,000.

Register entry

Telegram ID-1002257051470
TypeChannel
Username@daiyudexiaowo
CreatedBetween 1 October 2024 and 31 March 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded3 September 2026
Last confirmed live25 September 2026
Measurements held7
Confirmed unchanged1 time, most recently 25 September 2026
On Telegramt.me/daiyudexiaowo

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 25 September 2026 and assigned it the closest of 31 fixed categories, at 94% 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 why it has no browse page of its own yet.

Growth

2,8773,2653,0713 September 2026 — 2,877 subscribers3 September 2026 — 2,877 subscribers4 September 2026 — 2,919 subscribers9 September 2026 — 2,988 subscribers13 September 2026 — 3,000 subscribers16 September 2026 — 3,138 subscribers25 September 2026 — 3,265 subscribers3 September 202625 September 2026
7 measurements spanning 23 days, net +388. 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 2,819–3,323 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
25 Sept 2026, 21:223,265+127
16 Sept 2026, 23:583,138+138
13 Sept 2026, 04:153,000+12
9 Sept 2026, 15:572,988+69
4 Sept 2026, 14:412,919+42
3 Sept 2026, 05:322,877no change
3 Sept 2026, 05:152,877first reading

Engagement

19 posts held, back to 11 August 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 1 page of Telegram’s post history, 20 posts per page.

ERR · 30 days
5.25%
avg views ÷ 3,265 subscribers
Avg views / post
172
2 posts measured
Reaction rate
—
this channel exposes no reaction counts
Posts in window
2
of 19 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 3 September 2026
Posts held19 (11 August 2026 – 3 September 2026)
Views total343
Reactions total—
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken3 Sept 2026, 05:32 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
42s
Average length
14s

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

27 reactions across 9 posts, in 5 distinct kinds. The most used accounts for 63.0% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤1763.0%
👏414.8%
🥰414.8%
👍13.70%
💋13.70%

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 11 of the 19 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 27 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 19 most recent posts we hold, published 11 August 2026 to 3 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

24 Aug 2026, 13:08 UTC≈1,590 views5 reactionsread 3 September 2026
Forwarded from @whlou4

━━━━━━━━━━━━━━ 🌟 老师评价 🌟 ━━━━━━━━━━━━━━ 🏷️ #武昌 #6p #10pp #御姐 #大胸 #徐东 👤 老师:黛玉 (@daiyuxiao) 🔗 主页:https://t.me/wuhanhua1/19982?single ⭐ 综合:★★★★★ 5/5 ├ 🎯 技能:★★★★★ 5/5 ├ 💗 情绪:★★★★★ 5/5 ├ 🏡 环境:★★★★★ 5/5 └ 📷 人照:★★★★★ 5/5 📝 评价内容: 已经来过很多次了,老师休息了半年,也出击过其他老师,很多假照片的,看到黛玉老师回归赶紧出击了还是熟悉的味道,反正就一个字顶,人照无差,服务好,情绪价值拉满 ━━━━━━━━━━━━━━ 🙋 评价人:匿名 🕒 时间:2026-08-24 15:15 ━━━━━━━━━━━━━━ 黄鹤楼群 @wuhanlou 技术聊天 @whlou6 武汉东湖 @whlou 工兵优惠 @w…

❤5

24 Aug 2026, 07:11 UTC≈1,370 views0 reactionsread 3 September 2026
Forwarded from @whlou4

━━━━━━━━━━━━━━ 🌟 老师评价 🌟 ━━━━━━━━━━━━━━ 🏷️ #武昌 #6p #10pp #御姐 #大胸 #徐东 👤 老师:黛玉 (@daiyuxiao) 🔗 主页:https://t.me/wuhanhua1/19982?single ⭐ 综合:★★★★★ 5/5 ├ 🎯 技能:★★★★★ 5/5 ├ 💗 情绪:★★★★★ 5/5 ├ 🏡 环境:★★★★★ 5/5 └ 📷 人照:★★★★★ 5/5 📝 评价内容: 老师颜值很高 很御姐 环境很高档 进门就给了我一个拥抱 下次来武汉了再来 ━━━━━━━━━━━━━━ 🙋 评价人:匿名 🕒 时间:2026-08-24 14:55 ━━━━━━━━━━━━━━ 黄鹤楼群 @wuhanlou 技术聊天 @whlou6 武汉东湖 @whlou 工兵优惠 @whlou7 车评报告 @whlou4 查找老师 @vlchattbot

22 Aug 2026, 14:48 UTC≈1,410 views2 reactionsread 3 September 2026
Forwarded from @whlou4

━━━━━━━━━━━━━━ 🌟 老师评价 🌟 ━━━━━━━━━━━━━━ 🏷️ #武昌 #6p #10pp #御姐 #大胸 #徐东 👤 老师:黛玉 (@daiyuxiao) 🔗 主页:https://t.me/wuhanhua1/19982?single ⭐ 综合:★★★★★ 5/5 ├ 🎯 技能:★★★★★ 5/5 ├ 💗 情绪:★★★★☆ 4/5 ├ 🏡 环境:★★★★★ 5/5 └ 📷 人照:★★★★★ 5/5 📝 评价内容: 老师人照一致,五官标致,是个真美女,身材也很好,没有多余的肉,手感很舒服,抚摸下就有生理反应。服务热情大方,交流起来很顺畅。很不错的体验,还会再去的。 ━━━━━━━━━━━━━━ 🙋 评价人:匿名 🕒 时间:2026-08-22 20:07 ━━━━━━━━━━━━━━ 黄鹤楼群 @wuhanlou 技术聊天 @whlou6 武汉东湖 @whlou 工兵优惠 @whl…

❤2

21 Aug 2026, 03:34 UTC≈1,540 views4 reactionsread 3 September 2026
Forwarded from @whlou4

━━━━━━━━━━━━━━ 🌟 老师评价 🌟 ━━━━━━━━━━━━━━ 🏷️ #武昌 #6p #10pp #御姐 #大胸 #徐东 👤 老师:黛玉 (@daiyuxiao) 🔗 主页:https://t.me/wuhanhua1/19982?single ⭐ 综合:★★★★★ 5/5 ├ 🎯 技能:★★★★★ 5/5 ├ 💗 情绪:★★★★★ 5/5 ├ 🏡 环境:★★★★★ 5/5 └ 📷 人照:★★★★★ 5/5 📝 评价内容: 黛玉老师真的跟红楼梦里面的林黛玉一样,声音软软糯糯的,一进门就抱住你,女友感十足,后面的服务也非常到位,做完了还陪你聊天,满分评价,下次还会再来的。 ━━━━━━━━━━━━━━ 🙋 评价人:匿名 🕒 时间:2026-08-21 10:23 ━━━━━━━━━━━━━━ 黄鹤楼群 @wuhanlou 技术聊天 @whlou6 武汉东湖 @whlou 工兵优惠 @whlo…

❤4

Showing the 12 most recent of 19 posts we hold for @daiyudexiaowo. 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 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 25 September 2026 — this entry's latest reading, not the date you are reading this.

“黛玉的小窝” (@daiyudexiaowo), 3,265 subscribers as measured 25 September 2026. Telegram Register, tgregister.com/channel/daiyudexiaowo.

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.