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Telegram profile photo for 海洋hotel

Channel

海洋hotel

@Oceanhotel

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

16,471subscribers

-271 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 10,000–31,623.

Register entry

Telegram ID-1001678084303
TypeChannel
Username@Oceanhotel
CreatedBetween 1 December 2021 and 30 April 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live10 September 2026
Measurements held27
Confirmed unchanged1 time, most recently 10 September 2026
On Telegramt.me/Oceanhotel

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 10 September 2026 and assigned it the closest of 31 fixed categories, at 49% 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

16,18718,85317,5207 August 2026 — 16,742 subscribers8 August 2026 — 16,727 subscribers9 August 2026 — 18,853 subscribers10 August 2026 — 17,874 subscribers11 August 2026 — 17,866 subscribers12 August 2026 — 17,842 subscribers12 August 2026 — 17,815 subscribers14 August 2026 — 17,759 subscribers15 August 2026 — 17,725 subscribers16 August 2026 — 17,662 subscribers17 August 2026 — 17,617 subscribers19 August 2026 — 17,595 subscribers20 August 2026 — 17,563 subscribers21 August 2026 — 17,565 subscribers22 August 2026 — 17,503 subscribers24 August 2026 — 17,513 subscribers26 August 2026 — 16,231 subscribers27 August 2026 — 16,198 subscribers28 August 2026 — 16,187 subscribers29 August 2026 — 18,114 subscribers30 August 2026 — 17,745 subscribers31 August 2026 — 17,351 subscribers1 September 2026 — 17,171 subscribers2 September 2026 — 16,972 subscribers4 September 2026 — 16,836 subscribers7 September 2026 — 16,723 subscribers10 September 2026 — 16,471 subscribers16,4717 August 202610 September 2026
27 measurements spanning 34 days, net -271. 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 15,787–19,253 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 27
Measured (UTC)SubscribersChange
10 Sept 2026, 07:2116,471-252
7 Sept 2026, 03:0016,723-113
4 Sept 2026, 07:3916,836-136
2 Sept 2026, 23:5816,972-199
1 Sept 2026, 23:3817,171-180
31 Aug 2026, 22:2717,351-394
30 Aug 2026, 20:5317,745-369
29 Aug 2026, 17:5418,114+1,927
28 Aug 2026, 15:2416,187-11
27 Aug 2026, 12:3516,198-33
26 Aug 2026, 15:2716,231-1,282
24 Aug 2026, 09:1217,513+10
22 Aug 2026, 15:2717,503-62
21 Aug 2026, 02:4817,565+2
20 Aug 2026, 01:5617,563-32
19 Aug 2026, 02:0517,595-22
17 Aug 2026, 23:0617,617-45
16 Aug 2026, 20:5717,662-63
15 Aug 2026, 14:3717,725-34
14 Aug 2026, 04:5717,759first reading

Engagement

327 posts held, back to 7 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 55 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
0.449%
avg views ÷ 16,471 subscribers
Avg views / post
74.0
248 posts measured
Reaction rate
0.28%
reactions ÷ views · ER floor
Posts in window
248
of 327 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 22 of 248 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 September 2026
Posts held327 (7 August 20263 September 2026)
Views total18,359
Reactions total8
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken3 Sept 2026, 09:32 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
6m 42s
Average length
21s

Measured directly from 19 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

10 reactions across 10 posts, in 1 kind.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
10100.0%

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 30 of the 327 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 10 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 327 most recent posts we hold, published 7 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

3 Sept 2026, 07:50 UTC44 viewsread 3 September 2026
Forwarded from @Yauyuetspa2Photo

🇯🇵miwa日本妹超多好評😍😍🤙多謝各位哥哥支持

3 Sept 2026, 07:50 UTC49 viewsread 3 September 2026
Photo

🇯🇵Japan 全新 #日本妹 19歲大波Miwa 高質素好服務靚妹仔

3 Sept 2026, 07:50 UTC30 views1 reactionsread 3 September 2026
Photo

#日本妹 #miwa 真人真相🔥 隆重宣佈,重大消息❤️ #新人首次出現 又一個真正日本🇯🇵美女加盟 19歲 日本🇯🇵 高顏值妹妹 165高 真D大波 長腿馬甲線 蜜桃🍑 #粉紅Lin頭可遇不可求🤭 真正嫩口 皮膚白雪雪右嫩右滑超好摸 熱情主動秒速破冰🥳 車牌易考🚗 反應夠真實易動情🤤 配合度高唔識格手 有♻️💣吹奏 #全新第一次嚟香港返工 #日文+英文溝通、普通話 有埋驚喜服務💕 🌸💰家用🌸 😘A ) 1200/45min:1Q全 😘B ) 2200/90min :2Q全 😘nuru +200 😘口爆+200 😘 拍片+300(不露樣) 😘顏射+200 😘過夜:6000(00:00-09:00) TG預約: https://t.me/oceanhotelbooking https://t.me/Gemkiss168 睇相頻道:https://t.me/Oceanhotel Ws:+852 60848799

1

3 Sept 2026, 07:50 UTC37 viewsread 3 September 2026
Photo

健身中心:海洋 健身教練:Miwa日本妹 相頭:9/10 相9成 靚女靚妹仔,估唔到有咁細個㗎妹 身材:8/10 16x高走肥 堅挺青筋D波 服務:10/ 10 殘廢餐 應有盡有 Part 1:一入屋囡囡見到我就已經攬住車埋 黎,除衫沖涼,沖得好仔細,水蕭,主動幫手抹身,坐床邊幫手抹埋腳。 Part 2:上床按摩,波推,漫遊,貓式吹吹到雪雪聲。正面錫lin,望住我環吹,眼神勁淫,吹功一流,主動69,飽乾淨冇異味,囡好敏感,係咁震哂出水,忍唔住就上套 Part 3:女上騎士上身係咁un,轉男上,囡囡話好鍾意對住鏡做,之後轉狗仔對住塊鏡完場,最後仲有事後蕭。 落樓價:十二魚 預約安排(*如適用):秒回快覆 小插曲/特别分享(*如適用): 健身喜好(*如適用):靚女、好服務總結:外表服務性格一流,唔洗破冰好傾好笑容

3 Sept 2026, 06:33 UTC46 viewsread 3 September 2026
Photo

🇰🇷Korea 全新 #韓國 20歲大波Jina 高質素好服務靚妹仔$1200

2 Sept 2026, 14:47 UTC61 viewsread 2 September 2026
Photo

18歲白滑happy 而家有位有哥哥要嗎?🇻🇳❤️

2 Sept 2026, 12:56 UTC116 viewsread 2 September 2026
Photo

🇻🇳越南妹cathy 靚樣靚波,而家有位👍

2 Sept 2026, 11:37 UTC112 viewsread 2 September 2026
Photo

20歲紅牌韓國妹大波🇰🇷JinA 宜家有位有哥哥要嗎?

2 Sept 2026, 07:54 UTC137 viewsread 2 September 2026
Photo

而家有房有🇻🇳🇰🇷🇯🇵越南日本韓國哥哥快啲預約😘

2 Sept 2026, 04:24 UTC175 viewsread 2 September 2026
Photo

❤️#韓國妹Jina好評勁多👍❤️哥哥唔試就走寶🇰🇷🇰🇷🥰

Showing the 12 most recent of 327 posts we hold for @Oceanhotel. 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

Republished by

Channels on the register that have forwarded this channel's posts into their own feed.

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 4 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 10 September 2026 — this entry's latest reading, not the date you are reading this.

“海洋hotel” (@Oceanhotel), 16,471 subscribers as measured 10 September 2026. Telegram Register, tgregister.com/channel/Oceanhotel.

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.