#水果 我半夜饿了,吃了一个苹果。我吃了阿克苏苹果,味道真棒! 📺📺📺📺📺📺📺 👑葵花宝典:@KHBD 👑DJ频道:@DJ_777r 👑交流大群: @dnygjd777 💎AI辅助工具 : @khbd688 💎AI作图工具: @KHBD777 💎认知文化: @renzhiwenhua 🔵全球素材:@taiwansucai223 🔵商务/误封联系: @seven77i
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Channel
@taiwansucai223
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Posts recorded as deleted · Citations · Handles named that no longer answer · Telegram's recommendations · Cite this entry
10,799subscribers
-1,192 since we began measuring on 10 August 2026
Risers and fallers across the register · movement among entries of 10,000–31,623.
| Telegram ID | -1001672338473 |
|---|---|
| Type | Channel |
| Username | @taiwansucai223 |
| Description | 葵花宝典: @KHBD 唯一交流大群: @dnygjd777 何时葡萄先熟透,你要静候再静候 何时功成与名就,你要静心再静心 |
| Created | Between 1 December 2021 and 30 April 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 10 August 2026 |
| Last confirmed live | 9 November 2026 |
| Measurements held | 58 |
| Confirmed unchanged | 1 time, most recently 9 November 2026 |
| On Telegram | t.me/taiwansucai223 |
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 11 September 2026 and assigned it the closest of 31 fixed categories, at 46% 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 |
|---|---|---|
| 9 Nov 2026, 16:21 | 10,799 | -11 |
| 8 Nov 2026, 09:56 | 10,810 | -11 |
| 7 Nov 2026, 03:25 | 10,821 | -27 |
| 4 Nov 2026, 22:17 | 10,848 | -14 |
| 3 Nov 2026, 23:17 | 10,862 | -10 |
| 3 Nov 2026, 00:15 | 10,872 | -7 |
| 2 Nov 2026, 01:17 | 10,879 | -12 |
| 1 Nov 2026, 04:09 | 10,891 | -14 |
| 31 Oct 2026, 05:41 | 10,905 | -22 |
| 30 Oct 2026, 06:51 | 10,927 | -11 |
| 29 Oct 2026, 09:36 | 10,938 | -29 |
| 28 Oct 2026, 04:51 | 10,967 | -28 |
| 27 Oct 2026, 02:01 | 10,995 | -25 |
| 26 Oct 2026, 00:40 | 11,020 | -14 |
| 25 Oct 2026, 00:39 | 11,034 | -27 |
| 24 Oct 2026, 00:46 | 11,061 | -29 |
| 22 Oct 2026, 22:59 | 11,090 | -17 |
| 21 Oct 2026, 20:16 | 11,107 | -20 |
| 20 Oct 2026, 14:35 | 11,127 | -41 |
| 19 Oct 2026, 14:19 | 11,168 | first reading |
213 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 57 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.
| Window | Rolling 30 days · latest post in window 10 November 2026 |
|---|---|
| Posts held | 213 (9 August 2026 – 10 November 2026) |
| Views total | 12,497 |
| Reactions total | — |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 10 Nov 2026, 10:24 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 10 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 29 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.
16 reactions across 16 posts, in 1 kind.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 👍 | 16 | 100.0% |
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 16 of the 213 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 16 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 213 most recent posts we hold, published 9 August 2026 to 10 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 61 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).
#水果 我半夜饿了,吃了一个苹果。我吃了阿克苏苹果,味道真棒! 📺📺📺📺📺📺📺 👑葵花宝典:@KHBD 👑DJ频道:@DJ_777r 👑交流大群: @dnygjd777 💎AI辅助工具 : @khbd688 💎AI作图工具: @KHBD777 💎认知文化: @renzhiwenhua 🔵全球素材:@taiwansucai223 🔵商务/误封联系: @seven77i
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#晚餐 图1:今晚的晚餐!烤鸡腿、土豆泥,以及洋葱、大蒜、西兰花的蔬菜混合。 图2:煮熟的西兰花小花 / 脆皮鸡 / 荷兰酱。 📺📺📺📺📺📺📺 👑葵花宝典:@KHBD 👑DJ频道:@DJ_777r 👑交流大群: @dnygjd777 💎AI辅助工具 : @khbd688 💎AI作图工具: @KHBD777 💎认知文化: @renzhiwenhua 🔵全球素材:@taiwansucai223 🔵商务/误封联系: @seven77i
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#纽约 #日落 📖 在日落的陪伴下,阅读能治愈心灵。 《我所知道的一切关于爱》(Everything I Know About Love),作者:多莉·阿尔顿。每次阅读这本书,我都感觉内心深处那些未曾言说的情感正在慢慢展开。书中对二十岁出头的状态进行了精彩的描绘。周六下午,我喜欢在家的某个角落阅读,窗外是美丽的日落和曼哈顿的天际线,这种景象真的让人感到平静。 📺📺📺📺📺📺📺 👑葵花宝典:@KHBD 👑DJ频道:@DJ_777r 👑交流大群: @dnygjd777 💎AI辅助工具 : @khbd688 💎AI作图工具: @KHBD777 💎认知文化: @renzhiwenhua 🔵全球素材:@taiwansucai223 🔵商务/误封联系: @seven77i
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#调教 完整的套图来了 📺📺📺📺📺📺📺 👑葵花宝典:@KHBD 👑DJ频道:@DJ_777r 👑交流大群: @dnygjd777 💎AI辅助工具 : @khbd688 💎AI作图工具: @KHBD777 💎认知文化: @renzhiwenhua 🔵全球素材:@taiwansucai223 🔵商务/误封联系: @seven77i
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#调教 专用图片 📺📺📺📺📺📺📺 👑葵花宝典:@KHBD 👑DJ频道:@DJ_777r 👑交流大群: @dnygjd777 💎AI辅助工具 : @khbd688 💎AI作图工具: @KHBD777 💎认知文化: @renzhiwenhua 🔵全球素材:@taiwansucai223 🔵商务/误封联系: @seven77i
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#红酒 #葡萄酒 我打开了一瓶状况非常好的葡萄酒。🍷 Echezeaux 1991:颜色是美丽的宝石红,带有非常浓郁的果香🫐🍓🍒。从头到尾都非常浓郁,但又很优雅。在最后,矿物、皮革和烟草的味道会更加明显。保存得非常好👍 真幸运! 📺📺📺📺📺📺📺 👑葵花宝典:@KHBD 👑DJ频道:@DJ_777r 👑交流大群: @dnygjd777 💎AI辅助工具 : @khbd688 💎AI作图工具: @KHBD777 💎认知文化: @renzhiwenhua 🔵全球素材:@taiwansucai223 🔵商务/误封联系: @seven77i
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#水疗 我对这家店的环境和体验都非常满意。👍 美容师详细地向我介绍了我的身体状况,以及如何根据我的具体需求调整生活方式。从我走进这家店的那一刻起,我就感到非常自信,并且想要完全信任她。 - 进入楼上的私人房间后,环境非常舒适。 📺📺📺📺📺📺📺 👑葵花宝典:@KHBD 👑DJ频道:@DJ_777r 👑交流大群: @dnygjd777 💎AI辅助工具 : @khbd688 💎AI作图工具: @KHBD777 💎认知文化: @renzhiwenhua 🔵全球素材:@taiwansucai223 🔵商务/误封联系: @seven77i
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#早餐 我每天都期待着享用早餐。 📺📺📺📺📺📺📺 👑葵花宝典:@KHBD 👑DJ频道:@DJ_777r 👑交流大群: @dnygjd777 💎AI辅助工具 : @khbd688 💎AI作图工具: @KHBD777 💎认知文化: @renzhiwenhua 🔵全球素材:@taiwansucai223 🔵商务/误封联系: @seven77i
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#电影 #在家 周末晚上观看帕克斯顿的电影,真是太棒了。 ✅ 电影名称:我从未… 📺📺📺📺📺📺📺 👑葵花宝典:@KHBD 👑DJ频道:@DJ_777r 👑交流大群: @dnygjd777 💎AI辅助工具 : @khbd688 💎AI作图工具: @KHBD777 💎认知文化: @renzhiwenhua 🔵全球素材:@taiwansucai223 🔵商务/误封联系: @seven77i
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#散步 #高跟鞋 裸色鞋子非常适合浅色系的服装,也同样适合搭配深色系的服装。 6厘米的高跟鞋穿起来并不累,非常舒适。 📺📺📺📺📺📺📺 👑葵花宝典:@KHBD 👑DJ频道:@DJ_777r 👑交流大群: @dnygjd777 💎AI辅助工具 : @khbd688 💎AI作图工具: @KHBD777 💎认知文化: @renzhiwenhua 🔵全球素材:@taiwansucai223 🔵商务/误封联系: @seven77i
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#早餐 我刚吃完早餐!我吃了山姆会员店的坚果蜂蜜麦片,味道不错👍🏻,而且我很喜欢!非常饱腹。 📺📺📺📺📺📺📺 👑葵花宝典:@KHBD 👑DJ频道:@DJ_777r 👑交流大群: @dnygjd777 💎AI辅助工具 : @khbd688 💎AI作图工具: @KHBD777 💎认知文化: @renzhiwenhua 🔵全球素材:@taiwansucai223 🔵商务/误封联系: @seven77i
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我坚持每天早上和晚上都喝牛奶,但还是感觉皮肤没有变白。反而长了痘痘。现在闻到牛奶味就特别想吃…但我真的再也喝不下了。只能说,真的没有办法逆转黄黑肤色了! #牛奶 #人设 #话题 📺📺📺📺📺📺📺 👑葵花宝典:@KHBD 👑DJ频道:@DJ_777r 👑交流大群: @dnygjd777 💎AI辅助工具 : @khbd688 💎AI作图工具: @KHBD777 💎认知文化: @renzhiwenhua 🔵全球素材:@taiwansucai223 🔵商务/误封联系: @seven77i
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Showing the 12 most recent of 213 posts we hold for @taiwansucai223. 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 5 posts on @taiwansucai223 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.
Named by 20 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.
@taiwansucai223 named 1 handle 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.
The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.
This channel appears in 20 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
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 9 November 2026 — this entry's latest reading, not the date you are reading this.
“全球精品素材” (@taiwansucai223), 10,799 subscribers as measured 9 November 2026. Telegram Register, tgregister.com/channel/taiwansucai223.
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.