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Channel

夢幻女王SM會所(荔枝角)

@dreamworldSM

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

236subscribers

+22 since we began measuring on 29 September 2026

Risers and fallers across the register · movement among entries of Under 1,000.

Register entry

Telegram ID-1002263715634
TypeChannel
Username@dreamworldSM
Created28 February 2025 — measured — dated from the channel’s first post
First recorded29 September 2026
Last confirmed live5 October 2026
Measurements held3
Confirmed unchanged1 time, most recently 5 October 2026
On Telegramt.me/dreamworldSM

Growth

21423622529 September 2026 — 214 subscribers29 September 2026 — 214 subscribers5 October 2026 — 236 subscribers29 September 20265 October 2026
3 measurements spanning 6 days, net +22. 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 211–239 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
5 Oct 2026, 06:02236+22
29 Sept 2026, 13:22214no change
29 Sept 2026, 12:47214first reading

Engagement

6 posts held, back to 28 February 2025 — 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
43.6%
avg views ÷ 236 subscribers
Avg views / post
103
3 posts measured
Reaction rate
0.478%
reactions ÷ views · ER floor
Posts in window
5
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 3 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 29 September 2026
Posts held6 (28 February 2025 – 29 September 2026)
Views total309
Reactions total1
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken29 Sept 2026, 13:22 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.

Reaction mix

1 reaction across 1 post, in 1 kind.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤1100.0%

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 1 reactions 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 28 February 2025 to 29 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

29 Sept 2026, 06:00 UTC100 viewsread 29 September 2026

😀我們已在荔枝角重組SM工作室,歡迎各位朋友關注或😀推薦給有同樣喜好的朋友仔

29 Sept 2026, 05:40 UTC102 views1 reactionsread 29 September 2026

📝多元化SM特色餐牌📝 A餐|【女王調教.賤狗S&M虐戀】 60 分鐘 / 1,200💰 主打男S/女S與M受虐傾向調教,結合體罰與言語心理控制。 調教體驗:腳交調教、言語侮辱、踢JJ、吐口水、全身鞭打、賤狗角色扮演、性玩具調教 肢體服務:按摩、推前列腺、大波夾腸仔、制服絲襪誘惑 全套服務(含陪沖浴) B餐|【角色扮演.自製AV影音企劃】 60 分鐘 / 1,500💰 多元情境角色扮演,開放拍攝個人AV紀念影片,搭配輕重度道具。 角色變裝:護士、學生、空姐、後媽、扮女人(偽娘/女裝)、扮狗/扮馬 道具束縛:十字架綁捆、電棒刺激、強制射精 獨家特色:自由搭配劇情、可拍攝個人專屬AV留念 全套服務(含陪沖浴) C餐|【雙向女奴.莞式一條龍榨乾】 60 分鐘 / 1,800💰 主打SM 互動:女奴S&M雙向互玩、扮小狗、綑綁繩索、強姦遊戲情境 技巧玩法:東莞式一條龍、69姿勢、深喉吐納、情趣玩具 服務次數:口爆 1 次 + 做愛…

❤1

29 Sept 2026, 05:39 UTC107 views0 reactionsread 29 September 2026
Photo

👑夢幻女王SM會所👑 📱 #荔枝角 #九龍區 📌 #SM #工作室 #會所 👑 【女王降臨.重口味M系專屬支配領域】 專為渴望被征服、被玩弄、尋求極致刺激的你量身打造! 在這裡,你不需要尊嚴,只需要徹底臣服, 把靈魂與肉體全盤交出,體驗前所未有的高潮! ⛓️ 亮點一:【SM極限調教.打破感官底線】 全程心理與肉體雙重支配,徹底壓榨你的每一根神經: 尊榮賤狗模式: 繩藝嚴密捆綁、跪地爬行服從、69深度互玩、扮演忠誠賤奴 肢體與心理虐戀: 女王腳交踩踏、言語高壓侮辱、口水淋身洗禮、全軀鞭打狂歡 極限玩法解鎖: 制服絲襪後庭探秘、情趣玩具深度調教、情境角色扮演、深喉強制吞吐 雙重爆發體驗:不留餘地直接榨乾,保證讓你雙腿發軟、失魂落魄 💦 亮點二:【奢華水療水床.雙重濕滑激情】 除了重口調教,更享有頂級硬體帶來的水感肉欲饗宴: 大型按摩噴水鴛鴦浴:水花四濺的熱浪中,一邊享受深度水力按摩,一邊體驗「水中吹簫」與浴缸極致調情,浪潮滾…

Showing the 6 most recent of 6 posts we hold for @dreamworldSM. 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 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 5 October 2026 — this entry's latest reading, not the date you are reading this.

“夢幻女王SM會所(荔枝角)” (@dreamworldSM), 236 subscribers as measured 5 October 2026. Telegram Register, tgregister.com/channel/dreamworldSM.

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.