Channel
@jinbiany
On this record: Topic · Observations · Also posting the same content · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
106,578subscribers
-10,126 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 100,000–316,228.
| Telegram ID | -1002086501592 |
|---|---|
| Type | Channel |
| Username | @jinbiany |
| Description | 👉聚焦东南亚热点事件、国际新闻、社会动态、华人关注资讯，第一时间更新柬埔寨、斯里兰卡、缅甸、迪拜、马来西亚、泰国、越南、老挝等地区消息 |
| Created | Between 1 November 2023 and 31 May 2024— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 14 August 2026 |
| Measurements held | 9 |
| Confirmed unchanged | 1 time, most recently 14 August 2026 |
| On Telegram | t.me/jinbiany |
International news — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 10 August 2026 and assigned it the closest of 31 fixed categories, at 89% 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.
These are measurements, not verdicts. Each one below states something we counted, alongside the evidence it was counted from, so you can check it rather than take it. None of them is graded: every observation this register holds is recorded at severity 0, because the precision of the detectors behind them has not been measured yet, and a rating we cannot support is worse than none. Read each as a fact about the data, not as a judgement about the channel. How we measure.
Posts published here appear word for word on 6 other registered channels. They sit inside a group of 9 channels that share the same post bodies with each other. The matching is on the text itself, not on Telegram’s forward marker, so it finds a copy whether or not it was labelled as one.
| Posted first | Then | Overlap | Gap |
|---|---|---|---|
| @yuenanE/169436 Aug 2026, 13:26 UTC | @jinbiany/5863 · this entry6 Aug 2026, 13:26 UTC | 1.00 | under a minute |
| @jinbiany/5875 · this entry6 Aug 2026, 14:39 UTC | @yuenanE/169576 Aug 2026, 14:39 UTC | 1.00 | under a minute |
| @yuenanE/169596 Aug 2026, 15:20 UTC | @jinbiany/5876 · this entry6 Aug 2026, 15:20 UTC | 1.00 | under a minute |
| @yuenanE/169636 Aug 2026, 15:20 UTC | @jinbiany/5880 · this entry6 Aug 2026, 15:20 UTC | 1.00 | under a minute |
| @jinbiany/5882 · this entry6 Aug 2026, 15:41 UTC | @yuenanE/169656 Aug 2026, 15:41 UTC | 1.00 | under a minute |
| @jinbiany/5994 · this entry7 Aug 2026, 11:58 UTC | @yuenanE/170897 Aug 2026, 11:58 UTC | 1.00 | under a minute |
| Channel | Matching posts | Text overlap | Typical gap | Published first |
|---|---|---|---|---|
| @yuenanE | 18 (8/8 hand-verifiable sample passed) | 1.00 | under a minute | @yuenanE (18–0) |
| @chiguak | 18 (8/8 hand-verifiable sample passed) | 1.00 | under a minute | @chiguak (18–0) |
| @xigangz | 18 (8/8 hand-verifiable sample passed) | 1.00 | under a minute | @xigangz (18–0) |
| @Bx666x | 18 (8/8 hand-verifiable sample passed) | 1.00 | under a minute | @Bx666x (16–2) |
| @yuenanU | 14 (8/8 hand-verifiable sample passed) | 1.00 | under a minute | @yuenanU (10–4) |
| @miandianQ | 13 (8/8 hand-verifiable sample passed) | 1.00 | under a minute | @miandianQ (11–2) |
Text overlap is the Jaccard coefficient over the set of distinct three-word phrases in the two bodies: 1.00 is identical wording, and the threshold for counting a pair at all is 0.70. Candidates are generated by simhash LSH (4 x 16-bit bands, exact Hamming <= 3) verified against the bodies with Jaccard over the SET of distinct 3-word shingles. Published first counts which side of each matching pair carries the earlier timestamp — in this corpus, which is the limitation directly below.
What this cannot establish
MEASURED, DOMINANT ERROR SOURCE: a post ingested before 2026-08-06 may have carried a forward header that was not recorded. A 45-pair hand-check against live t.me pages found 14 (31%) where the live page shows a forward header naming the other channel and the database has none, plus 4 more (9%) naming a third party. The text match itself was wrong 0 times out of 45. Read attribution_capture.items_in_trusted_window before treating the unattributed count as a claim.
Telegram lets a channel forward a post with a header naming the source, and we only began reliably recording that header on 2026-08-06. 91 of the 91 matches recorded here fall after that date and carried no header when we read them. The rest predate reliable capture and are not evidence either way.
“Published first” means first in this corpus. We hold 32 comparable posts for this entry, running 6 August 2026 to 7 August 2026. A channel we have read one page deep will look younger than a neighbour we have read in full, and the order would flip with no change in the underlying facts.
The detector’s own notes on this observation, as it recorded them. Names in this_style are fields of the underlying evidence record, which the plain-English paragraphs above read out for this entry.
Across the whole group of 9, the earliest publisher we hold is @miandianQ. That is a statement about our reading window, not a claim of authorship.
Recorded under the key clone_copy, last confirmed 8 August 2026. An observation that a later pass no longer finds is cleared, and a cleared observation is removed from this page rather than being shown struck through — we do not keep publishing a claim we have withdrawn. Dispute an observation.
This channel’s posts match, word for word or near enough, posts on 8 other registered channels, found by comparing text fingerprints across every channel on the register. That matching has been checked by hand against the live Telegram pages and found reliable — 0 wrong of 45 pairs re-read.
Which channel, if either, published first is deliberately not shown. The same hand-check found that reading wrong 18 of 45 times — 60%, no better than a coin flip — because it depends on how deep our own crawl happened to reach into each channel’s history, not on when the content was actually first posted. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Word-for-word matching has several ordinary explanations besides copying — a channel mirroring itself, an unattributed repost, or two channels independently repeating the same wire story — and this measurement cannot tell those apart. How this is measured.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 14 Aug 2026, 19:16 | 106,578 | -31 |
| 13 Aug 2026, 12:08 | 106,609 | -21 |
| 12 Aug 2026, 12:44 | 106,630 | -44 |
| 11 Aug 2026, 14:37 | 106,674 | -22 |
| 10 Aug 2026, 14:14 | 106,696 | -21 |
| 9 Aug 2026, 15:17 | 106,717 | -15 |
| 8 Aug 2026, 18:47 | 106,732 | -9,548 |
| 7 Aug 2026, 16:35 | 116,280 | -424 |
| 6 Aug 2026, 17:32 | 116,704 | first reading |
214 posts held, back to 6 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 21 pagesof 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 3 of 213 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 14 August 2026 |
|---|---|
| Posts held | 214 (6 August 2026 – 14 August 2026) |
| Views total | 1,429 |
| Reactions total | 2 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 14 Aug 2026, 19:37 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 August 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 64 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.
2 reactions across 2 posts, in 2 distinct kinds. The most used accounts for 50.0% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 1 | 50.0% | |
| 👍 | 1 | 50.0% |
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 3 of the 214 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 2reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 214 most recent posts we hold, published 6 August 2026 to 14 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.
柬埔寨西港第三区发生一起员工维权事件。 8月14日晚，据悉，数名在韩国人经营的Wawuk赌场（位于一栋建筑四楼）工作的员工因长期遭遇工资拖欠问题，聚集现场进行抗议，要求雇主解决薪资问题。 目前，事件具体涉及人数、拖欠金额以及雇主方面的回应尚未公布。相关情况仍有待进一步调查核实。 👉东南亚大事件: @kk888 👉东南亚吃瓜群: @kk999 👉东南亚素材库: @zhaopian 👉投稿澄清爆料: @Bnnc888
🇺🇸 特朗普签署备忘录：允许私企对境外跨国犯罪组织实施网络攻击 美国白宫8月12日消息：特朗普签署《扩大打击跨国网络犯罪的能力》总统备忘录，援引第14390号行政令设立专项项目，吸纳私营企业参与打击境外跨国网络犯罪。 该项目由国土安全部国家协调中心负责，企业可开展两类网络行动：网络监视搜集威胁情报，以及对犯罪组织网络实施篡改、阻断、摧毁等处置。 参与企业须通过审查、签署法律协议，并缴纳不少于100万美元保证金。每一次行动都需要司法部、国土安全部书面批准，企业不得自行选定打击目标。 备忘录明确约束：禁止可能造成人员伤亡的行动；仅可针对非国家跨国犯罪组织，不得针对外国政府及国家支持的黑客实体，尽量规避第三方关键基础设施；若意外波及美国网络或公民，企业需立刻停止并上报。 司法部与国土安全部需在60天内出台实施细则，参与企业每年报送行动情况，相关部门向总统提交年度评估报告。 👉东南亚大事件: @kk888 👉东南亚吃瓜群:…
#最新消息：昨天柬埔寨波贝又抓了147人 执法人员发现133名外国人（51名女性），分属三个国籍，包括82名越南籍（26名女性）、18名中国籍（2名女性）和33名泰国籍（16名女性）。此外，还有14名柬埔寨籍（7名女性）。 查获大量涉嫌技术诈骗的物品：207部手机、3台笔记本电脑、31个CPU、97台显示器、313台一体机电脑和8张工作证。 👉东南亚大事件: @kk888 👉东南亚吃瓜群: @kk999 👉东南亚素材库: @zhaopian 👉投稿澄清爆料: @Bnnc888
轻信“缅北高薪赚大钱”陷入电诈团伙，因业绩不达标遭暴力惩罚 一名男子轻信“缅北高薪、轻松赚大钱”的虚假宣传，被诱骗进入电诈团伙。进入窝点后，不仅被迫从事诈骗活动，还因“业绩不达标”遭到团伙成员暴力惩罚，处境十分危险。 警方及相关机构多次提醒，所谓“缅北高薪工作”“轻松赚大钱”往往暗藏诈骗和非法拘禁等风险。切勿轻信陌生人的高薪诱惑，更不要为了所谓的“快速致富”冒险前往高风险地区。 👉东南亚大事件: @kk888 👉东南亚吃瓜群: @kk999 👉东南亚素材库: @zhaopian 👉投稿澄清爆料: @Bnnc888
#柬埔寨资讯：柴桢省发生丈夫砍死妻子案件 男子事后上吊身亡 今晚，柬埔寨柴桢省 Svay Chrum 县 Thmor Sar 村发生一起严重家庭暴力案件。一名女子遭丈夫持刀砍伤，因颈部受到严重伤害，当场死亡。 据当地消息称，案件发生后，涉事男子随后被发现上吊身亡。目前，警方及相关部门已介入调查，并对事件经过展开进一步核实。 据了解，事发前夫妻双方曾发生冲突，但双方究竟因何原因产生矛盾，并最终酿成妻子死亡、丈夫自杀的悲剧，目前仍有待警方进一步调查确认。 👉东南亚大事件: @kk888 👉东南亚吃瓜群: @kk999 👉东南亚素材库: @zhaopian 👉投稿澄清爆料: @Bnnc888
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#网友投稿：金三角特区“山水酒店”刚刚被治安局突击检查了，现场又有办公的被抓住了！ 现在山水酒店门口被治安局守着，想出酒店一律检查手机的内容，大家先不要去一楼！ 今天下午还有十几辆警察的车队进驻特区，听说是万象下来的督导工作组，最近风声太紧了，随时都会被抽查，在特区的各位吴彦祖们房间里不要放手机电脑！ 👉东南亚大事件: @kk888 👉东南亚吃瓜群: @kk999 👉东南亚素材库: @zhaopian 👉投稿澄清爆料: @Bnnc888
#网友投稿：金三角特区内的物业已经陆续开始发出通知。 物业会不定时抽查，发现电诈会直接上报治安局（抽查估计会包括证件问题）。 PS:特区内的小伙伴还好吗，被逮住就要天天吃稀饭白馒头了 👉东南亚大事件: @kk888 👉东南亚吃瓜群: @kk999 👉东南亚素材库: @zhaopian 👉投稿澄清爆料: @Bnnc888
洪森：在网上辱骂女性将被起诉 柬埔寨参议院主席洪森8月14日表示，柬埔寨一些社交媒体用户，包括网络卖家，经常使用诽谤、侮辱和谩骂等不当语言，无论是夫妻之间的家庭纠纷还是情侣之间的纠纷，都存在谩骂他人、甚至侮辱领导人和国家机构的情况，这导致社会价值观下降。 洪森要求妇女事务部今后针对网络辱骂女性的案件主动提起诉讼，即使涉及个人纠纷也不能置之不理。 PS：中国同胞要特别注意 特别是那些出口国粹的这类人 👉东南亚大事件: @kk888 👉东南亚吃瓜群: @kk999 👉东南亚素材库: @zhaopian 👉投稿澄清爆料: @Bnnc888
#群友爆料：报瓦交克雷度假村，全都是黑公司，高价赔付，赔付拉满。里面全是做国盘的，希望早上拔出此园区。 妙瓦底那边的公司都搬这里来了，希望中方关注，DKBA保护。交克附近园区基本上都清空了，而这里每天都有公司搬进来。这里号称比KK园区还硬，国内很多失踪、被绑架的人被送到这里，未成年人都有，还有很多女孩子，各个国家的都有。 这里面基本上都是国内盘、资金盘，军包，公司打死人，园区物业都不会管。希望中国警察、FBI快点来解救这里的同胞。 👉东南亚大事件: @kk888 👉东南亚吃瓜群: @kk999 👉东南亚素材库: @zhaopian 👉投稿澄清爆料: @Bnnc888
#干货分享：狗推反侦察篇之如何面对审讯 很多推子回国在里面撑不过几轮问话，就是因为不知道对方在用什么方法。今天把审讯室里最常见的套路拆开讲，希望各位分析师学会了都能应对 一、环境施压：从进门的瞬间就开始了 你走进审讯室的那一刻，压力就已经开始了。 封闭的空间：没有窗户、没有时钟，你感知不到时间的流逝，这种“失重感”会让人极度焦虑。 不对等的位置：你的椅子通常是固定的、低矮的，办案人员的桌椅更高、更舒适，一高一低之间，心理落差就出来了。 冰冷的氛围：灯光、墙壁、桌椅，一切都是冷色调的。这就是“情境营造法”，通过严肃的审讯环境对你形成心理震慑。 形体语言施压：审讯人员可能会用逼视的目光直视你、用手指叩击桌面，这些动作都在给你施加心理压力，让你感受到“威慑力量”。 你的策略：意识到这些都是“环境设计”，不是针对你个人的。保持冷静，不要被氛围吓住。 二、信息不对称战术：让你自己吓自己 你在里面，不知道外面发生了什么；你…
#群友投稿：金边《城际酒店》黑心商家，还是华住会旗下的，专门逮着中国人坑。避雷，真的避雷！只要是中国人，都离这个酒店远一点。 在这个酒店里住了10天，枕套上有污渍，要赔90美金，完全就是漫天要价。 第一天的时候，朋友来找我玩，他抽烟的时候把烟灰缸打翻了，弄到了被子上还有床单上。我叫来了前台工作人员，赔了30美金，很合理。毕竟弄脏了，清洗也麻烦。 然后住了两天以后，玻璃自爆了。自爆的时候，我立马叫来了工作人员保护现场，担心最后赖到我身上。结果还是要赔钱。 一开始，玻璃门要赔500美金，最后谈下来赔了300美金。 最可恨的是，我叫打扫房间的人来打扫卫生，他看到枕头套上有一点点污渍，都没有渗透到枕芯里面。可能就是在房间里吃东西的时候，不小心抹了一滴油上去，而且颜色很淡，不仔细看根本都看不到。 结果那个打扫房间的人立马叫前台过来，跟我说枕套上面有污渍，要我赔90美金。 一天的房费才80美金，一个枕套他敢要90美金，是想钱想…
Showing the 12 most recent of 214 posts we hold for @jinbiany. 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 — 405,940 of 1,345,403entries 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.
Named by 11 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.
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 14 August 2026 — this entry's latest reading, not the date you are reading this.
“东南亚大事件 柬埔寨大事件 柬埔寨新闻” (@jinbiany), 106,578 subscribers as measured 14 August 2026. Telegram Register, tgregister.com/channel/jinbiany.
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.