回不去的老家秋冬 #回不去的故乡 #初雪的记忆 #雪一落就美成了诗 #大雪后的农村景象 #故乡的画卷 #农村的冬天 #故乡下雪了
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Channel
@liaoku
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Posts recorded as deleted · Citations · Handles named that no longer answer · Cite this entry
50,516subscribers
+8,776 since we began measuring on 11 August 2026
Risers and fallers across the register · movement among entries of 31,623–100,000.
| Telegram ID | -1001723913990 |
|---|---|
| Type | Channel |
| Username | @liaoku |
| Description | 每日持续更新海外素材丨永久ID @Liaoku #素材 #套图 #海外素材 #东南亚 投稿 @uini8 📺海外大事件 :@haiwai7777 💧狗推精聊大学 :@daxue8 |
| Created | Between 1 December 2021 and 30 April 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 11 August 2026 |
| Last confirmed live | 12 November 2026 |
| Measurements held | 60 |
| Confirmed unchanged | 1 time, most recently 12 November 2026 |
| On Telegram | t.me/liaoku |
Travel — 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 9 September 2026 and assigned it the closest of 31 fixed categories, at 57% 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 |
|---|---|---|
| 12 Nov 2026, 01:08 | 50,516 | -386 |
| 10 Nov 2026, 06:09 | 50,902 | -440 |
| 8 Nov 2026, 14:58 | 51,342 | -204 |
| 7 Nov 2026, 11:30 | 51,546 | -263 |
| 6 Nov 2026, 13:20 | 51,809 | +408 |
| 5 Nov 2026, 16:30 | 51,401 | +1,616 |
| 4 Nov 2026, 14:54 | 49,785 | +796 |
| 3 Nov 2026, 13:18 | 48,989 | +2,976 |
| 2 Nov 2026, 13:50 | 46,013 | +3,742 |
| 1 Nov 2026, 12:26 | 42,271 | +4,259 |
| 31 Oct 2026, 15:55 | 38,012 | -347 |
| 30 Oct 2026, 14:38 | 38,359 | -470 |
| 29 Oct 2026, 12:44 | 38,829 | -328 |
| 28 Oct 2026, 13:41 | 39,157 | -426 |
| 27 Oct 2026, 13:06 | 39,583 | -288 |
| 26 Oct 2026, 13:30 | 39,871 | -510 |
| 25 Oct 2026, 09:54 | 40,381 | +3,098 |
| 24 Oct 2026, 10:09 | 37,283 | +5,866 |
| 23 Oct 2026, 12:39 | 31,417 | -161 |
| 22 Oct 2026, 13:20 | 31,578 | first reading |
376 posts held, back to 9 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 179 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 107 of 121 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 13 November 2026 |
|---|---|
| Posts held | 376 (9 August 2026 – 13 November 2026) |
| Views total | 81,947 |
| Reactions total | 34,738 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 14 Nov 2026, 05:22 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.
Lifetime counters from Telegram’s own channel header, read 14 November 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.
Measured directly from 73 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.
123,184 reactions across 328 posts, in 20 distinct kinds. The most used accounts for 15.5% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 👍 | 19,117 | 15.5% | |
| 🔥 | 18,492 | 15.0% | |
| ❤ | 15,618 | 12.7% | |
| 🎉 | 15,280 | 12.4% | |
| 😁 | 12,351 | 10.0% | |
| 💯 | 8,006 | 6.50% | |
| 👌 | 5,552 | 4.51% | |
| ❤🔥 | 3,657 | 2.97% | |
| 🥰 | 3,121 | 2.53% | |
| 🐳 | 3,079 | 2.50% | |
| 😍 | 3,064 | 2.49% | |
| ⚡ | 2,865 | 2.33% | |
| 🕊 | 2,863 | 2.32% | |
| 👏 | 2,764 | 2.24% | |
| 😘 | 2,537 | 2.06% | |
| 🤩 | 2,431 | 1.97% | |
| 😎 | 2,282 | 1.85% | |
| 😱 | 37 | 0.03% | |
| 🤬 | 37 | 0.03% | |
| 😢 | 31 | 0.025% |
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 331 of the 376 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 123,184 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 376 most recent posts we hold, published 9 August 2026 to 13 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: 0 of 121 posts held from the last 30 days (0%) 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).
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第二十七站 尼斯 Day 1|尼斯市区 尼斯圣母圣殿 → 马塞纳广场 → 萨雷雅集市 → 尼斯老城区 → 尼斯主教堂 → 城堡山 → 尼斯战争纪念碑 → I LOVE NICE 标牌 → 蓝椅子雕塑 → 英国人漫步大道海边日落;另圣女贞德教堂、俄罗斯东正教圣尼古拉主教座堂 Day 2|尼斯 → 芒通 → 摩纳哥 → 埃兹 → 返回尼斯 芒通:尼斯乘火车到芒通站 → 萨布莱特海滩 → 芒通全景观景点 → 圣米歇尔网红楼梯 → 圣米歇尔大教堂 → 艺术家小巷 → 港口观景台 → 圣米歇尔街 摩纳哥:乘火车到摩纳哥蒙特卡洛站 → 拉沃托海滩 → 赫库勒斯港 → 圣马丁花园 → 海洋博物馆 → 圣母无原罪主教座堂 → 王子宫殿 埃兹:乘火车到埃兹站,上山到埃兹山顶村 → 埃兹城堡遗迹 → 埃兹站乘火车返回尼斯 Day 3|昂蒂布 → 戛纳 昂蒂布:尼斯乘火车到昂蒂布火车站→ 马里埃维拉摄影点打卡 → 环海徒步【非常夯】→ 城堡 → 莫奈…
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西西里第四章 城市漫游 大巴到Catania,火车站里老城有点距离的 休整后在老城区闲逛喝咖啡~修道院改造成大学的建筑蛮惊艳的图4️⃣ 第二天火车去Taormina,站台是影视剧场景,以小镇来说这里比其他火车站精致很多,一路爬山视野越来越开阔,还看到了远方的Etna火山🌋,小镇各种名品店,路过D&G冠名的咖啡店一杯espresso8️⃣欧~^_^~ 走过路过就错过 中午吃了个很香的西西里黑猪肉白披萨,除了肉少价贵没毛病~没带充电宝的我 手机快没电要往回赶路了看不了希腊剧院[叹气R]那就留给下次了可以从墨西拿方向进来 #西西里岛 #Catania #陶尔米纳
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Showing the 12 most recent of 376 posts we hold for @liaoku. 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.
We recorded 1 post on @liaoku 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.
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.
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.
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.
@liaoku named 4 handles 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 12 November 2026 — this entry's latest reading, not the date you are reading this.
“东南亚海外素材” (@liaoku), 50,516 subscribers as measured 12 November 2026. Telegram Register, tgregister.com/channel/liaoku.
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.