Telegram RegisterThe public register of Telegram

Channel

新手💕外約需知

@xm956

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

1,273subscribers

+31 since we began measuring on 7 August 2026

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

Register entry

Telegram ID-1001675322498
TypeChannel
Username@xm956
CreatedBetween 1 December 2021 and 31 March 2023— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live11 August 2026
Measurements held4
Confirmed unchanged1 time, most recently 11 August 2026
On Telegramt.me/xm956

Growth

1,2421,2731,257.57 August 2026 — 1,242 subscribers7 August 2026 — 1,242 subscribers7 August 2026 — 1,243 subscribers11 August 2026 — 1,273 subscribers7 August 202611 August 2026
4 measurements spanning 4 days, net +31. 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 1,237–1,278 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
11 Aug 2026, 04:321,273+30
7 Aug 2026, 23:521,243+1
7 Aug 2026, 05:001,242no change
7 Aug 2026, 04:491,242first reading

Engagement

9 posts held, back to 15 September 2024the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 pageof Telegram’s post history, 20 posts per page.

ERR · 30 days
9.37%
avg views ÷ 1,273 subscribers
Avg views / post
119
3 posts measured
Reaction rate
1.61%
reactions ÷ views · ER floor
Posts in window
3
of 9 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 1 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 3 August 2026
Posts held9 (15 September 20243 August 2026)
Views total358
Reactions total2
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken7 Aug 2026, 05:00 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

33 reactions across 6 posts, in 3 distinct kinds. The most used accounts for 87.9% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
2987.9%
👍39.09%
😁13.03%

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 9 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 33reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 9 most recent posts we hold, published 15 September 2024 to 3 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

3 Aug 2026, 08:44 UTC124 views2 reactionsread 7 August 2026
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💖台灣天堂島外送服務區域💖 ✅本茶坊只有外送/外約服務 ❌不是定點|無定點‼️ 🤯🤬😣😫🤯🤬😣😫 ✅ 北部服務區域 ⚡️ 台北市(4500起) 🔤 熟客可安排住家 「中正區|中山區|萬華區|大同區」 「松山區|大安區|信義區|內湖區」 「南港區|士林區|北投區|文山區」 ⚡️ 新北市(4500起) 🔤 熟客可安排住家 「板橋區|汐止區|新店區|永和區」 「中和區|土城區|三重區|新莊區」 「瀘洲區|五股區|泰山區」 「淡水|八里|林口|龜山+200車資」 ⚡️ 新竹市(4500起) 「新竹市|竹北區|東區|北區|香山」 🤯🤬😣😫🤯🤬😣😫 ✅ 中部服務區域 ⚡️ 台中市(3000起) 🔤 熟客可安排住家 「東區|西區|南區|北區|中區」 「西屯區|南屯區|北屯區|太平區」 「大里區|烏日區|大雅區」 「豐原區|沙鹿區 + 200車資」 🤯🤬😣😫🤯🤬😣😫 ✅ 南部服務區域 ⚡️ 高雄市(3200起) 「左營|三民|

2

3 Aug 2026, 08:36 UTC105 viewsread 7 August 2026
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如何向茶姐提供自己的需求? 天堂島約會的格式流程👇 請按照以下格式填寫,表達自己的要求 越詳細迷妹越好幫你物色符合的女生 迷妹家喝茶預約格式 目前地區: 妹妹類型: 身材要求: 討厭禁忌: 目前預算: 希望服務: 想約幾節: 預約時間: 哪家旅館: 一律見面滿意現金消費 不喜可退換 ➖➖➖➖🎀➖➖➖➖ 📱 私訊:@xmi_999 ⭐ Gleezy:xmi999(下載app) 📱 官網:http://www.xmi999.com/

3 Aug 2026, 08:32 UTC129 viewsread 7 August 2026
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📢最簡單明了の約會流程: ✨ ①.告知您方便的縣市、喜歡的類型、方便的時間以及預算範圍,我會給您提供合理的建議和合適的妹妹供您挑選 ✨②.小迷會再次確認時間、地點、妹妹、價位,然後馬上幫您安排或預約,避免您在旅館等待時間過長 ✨③.如果有提前預約,請您在預約的時間內提供房號給小迷,小迷把房號提供給妹妹,稍作休息後妹妹會直接到房間找您 ✨ ④.妹妹抵達房間後,一律見面現金交易(不轉賬、不匯款、不買點數),如果有任何疑問或者對來服務的妹妹不滿意,可以馬上聯絡小迷處理退換哦 ✨PS:如若臨時有事需要取消,請一定要提前告知,小迷好及時做應變處理,相互理解 感恩❤️ 🎀迷妹營業時間: 下午13:00-凌晨04:00 ➖➖➖➖🎀➖➖➖➖ 📱 私訊:@xmi_999 ⭐ Gleezy:xmi999(下載app) 📱 官網:http://www.xmi999.com/

22 May 2026, 07:21 UTC716 viewsread 7 August 2026
Forwarded from @yun9782Photo

防丟失 | 通知‼️ 辛苦大家加一下我的Gleezy唷 ⭐ Gleezy:xmi999 請大家同步添加~ 🤗🤗 如果TG找不到我可以去Gleezy找我喔 🐾🐾🐾🐾💗💗💗🐾🐾🐾🐾 💥台灣天堂島喝🍵群組 連結:https://c.gleezy.top/ffnSSeIH 射後💦心得客評專區 連結:https://c.gleezy.top/m5e7oLRe 新手💕外約需知 連結:https://c.gleezy.top/ZdrSjK4L 班表群 掃碼添加或是點擊連結加入喔 如果進不去 可以先加我 我拉你進去💗

3 Mar 2025, 12:05 UTC≈21,100 views8 reactionsread 7 August 2026
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🦋天堂島外送茶莊-【起跳價錢】 北部-【台北-新北-新竹】 #起跳價錢:4500一節 時間:4500至7000一節50分鐘一次 時間:7500以上的價錢一節60分鐘一次 中部-【台中-彰化-南部】 #起跳價錢:3000一節 時間:3000至4000一節40分鐘一次 時間:5000至7000一節50分鐘一次 時間:8000以上的價錢一節60分鐘一次 南部-【台南-高雄】 #起跳價錢:3200一節 時間:3200至7000一節40分鐘一次 時間:8000至9000一節50分鐘一次 時間:10000以上的價錢一節60分鐘一次 一節是一次 二節是二次 時間疊加 三節是三次 時間疊加 以此類推~~ 如果不懂時間疊加可來密我詳細了解 📱 加賴:999xmik 📱 私訊:@xmi_999 📱 小號:@TWkk999 📱 官網:http://www.xmi999.com/

6👍1😁1

4 Feb 2025, 17:21 UTC≈3,820 views4 reactionsread 7 August 2026

📢 約妹注意事項 1.我這裡的妹妹都是外約旅館或者是住家的或者是飯店 不是定點喔‼️ 2.外約旅館是您開房間,不是我這邊開,你開了房間之後給我房號唷‼️ 3.如果開好房間突然臨時跟小迷殺價,小迷會把原先定的高價位女生叫回來,然後再安排一位符合你預算的女生過去🐾 4.請男生紳士一些,請對我家妹妹溫柔一些,(如果是妹妹的態度不好,麻煩請立即找小迷,小迷來處理,不要生氣氣 請勿動怒)💦💦💦

4

24 Dec 2024, 09:21 UTC≈4,120 views8 reactionsread 7 August 2026
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📌 雙飛是什麽? 雙飛=3p 顧名思義就是3個人一起玩的意思 本茶莊只限一男兩女的玩法 也就是一王兩後~ 讓你體驗帝王般的感覺 📌 雙飛注意事項? ①、熟客才可以約3P ②、不可無套,必須帶套 ③、雙飛一節只能射一次 ④、只接受一王兩後的玩法 (多p也可以接受,限一男多女) 雙飛有什麽姿勢可以玩? #姿勢一:狂熱之夢 首先從後方進入A女,將她的大腿往後勾著你的屁股,B女則處在你們中間,好進行一些口交動作(圖一) #姿勢二:傀儡大師 兩女側躺面對面親熱,雙腿交纏在一起,你則跪在他們之間,邊進入A女進行性愛動作,邊用手指愛撫B女,同時滿足三方的飢渴慾望(圖二) #姿勢三:觀看與學習 顧名思義就是當A女幫B女口交時,你可以跪坐在A女雙腿上方,一方面自己打手槍,另一方面學習她們是如何運用口技來滿足彼此,畢竟只有女人最懂女人,舔哪裡才舒服她們最清楚了(圖三) #姿勢四:完美三明治 最常見的3P姿勢之一, 兩女彼此交疊在一起,你從

8

15 Sept 2024, 09:24 UTC≈6,370 views2 reactionsread 7 August 2026
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#小迷家地區詳細車資表 以上的地區需要車資 其他地區不需要車資 ⋯⋯⋯⋯ʕ •ᴥ•ʔ⋯⋯⋯⋯ 📱 賴:999xmik 📱 卡緊密我: https://t.me/xmi_999 ⋯⋯⋯⋯ʕ •ᴥ•ʔ⋯⋯⋯⋯ 🕯加入天堂島頻道總覽 https://t.me/TTD977 💝官網: http://www.xmi999.com/

2

15 Sept 2024, 09:22 UTC≈7,160 views9 reactionsread 7 August 2026
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🥳🥳北中南服務地區 這些都是有服務的地區唷 如果你不在以上地區👆 請看以下地區格式👇 🎀無服務地區 🎀方便到地區 🈚️台東 👉高雄 🈚️苗栗 👉新竹-台中 🈚️屏東 👉高雄-台南 🈚️桃園-中壢 👉林口-龜山-新竹 🈚️基隆 👉台北-南港-汐止 🈚️花蓮 👉台中-南投-高雄 🈚️嘉義 👉台南-高雄-南投 🈚️樹林 👉新莊-板橋-土城 🈚️三峽 👉土城-新店 🈚️宜蘭 👉台北-新北-台中 🈚️旗津 👉前鎮-小港 🈚️安平區 👉中西區-北-東-南 🈚️安南區 👉永康-北-中西 🈚️鹽程區

7👍2

Showing the 9 most recent of 9 posts we hold for @xm956. 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.

Citation-graph rank

Citation-graph rank — 26,314 of 1,160,990entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.

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 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.

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.

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.

“新手💕外約需知” (@xm956), 1,273 subscribers as measured 11 August 2026. Telegram Register, tgregister.com/channel/xm956.

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.