#网友投稿:柬埔寨警方已和中国公安实现数据共享,范围涵盖柬埔寨出入境记录、在柬中国人居住登记、各类实名登记信息等。 请在柬同胞们遵守当地法律法规,请勿从事任何违法犯罪活动 🔔 点击订阅缅北通缉令频道 👉 t.me/+bO3VCrsaPyU0MzI1 ☎️ 投稿爆料联系: @pige
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Channel
@xinwen811
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Telegram's recommendations · Cite this entry
203,615subscribers
-4,365 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 100,000–316,228.
| Telegram ID | -1001812714663 |
|---|---|
| Type | Channel |
| Usernames | @dny1111 @mbsss @xinwen811 |
| Created | Between 1 October 2022 and 30 September 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 8 November 2026 |
| Measurements held | 173 |
| Confirmed unchanged | 1 time, most recently 8 November 2026 |
| On Telegram | t.me/xinwen811 |
Gambling & betting — 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 8 August 2026 and assigned it the closest of 31 fixed categories, at 59% 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 |
|---|---|---|
| 8 Nov 2026, 22:20 | 203,615 | -650 |
| 8 Nov 2026, 10:40 | 204,265 | -156 |
| 8 Nov 2026, 07:11 | 204,421 | -482 |
| 7 Nov 2026, 17:49 | 204,903 | -349 |
| 7 Nov 2026, 07:37 | 205,252 | -279 |
| 7 Nov 2026, 02:18 | 205,531 | -372 |
| 6 Nov 2026, 14:29 | 205,903 | -145 |
| 6 Nov 2026, 09:21 | 206,048 | -182 |
| 6 Nov 2026, 04:05 | 206,230 | -275 |
| 5 Nov 2026, 17:38 | 206,505 | -91 |
| 5 Nov 2026, 12:36 | 206,596 | -378 |
| 5 Nov 2026, 04:29 | 206,974 | -378 |
| 4 Nov 2026, 18:38 | 207,352 | -111 |
| 4 Nov 2026, 11:04 | 207,463 | -70 |
| 4 Nov 2026, 06:34 | 207,533 | -474 |
| 3 Nov 2026, 21:07 | 208,007 | -617 |
| 3 Nov 2026, 10:17 | 208,624 | -111 |
| 3 Nov 2026, 07:41 | 208,735 | -664 |
| 2 Nov 2026, 19:27 | 209,399 | -431 |
| 2 Nov 2026, 09:19 | 209,830 | first reading |
2,767 posts held, back to 7 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 190 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 474 of 685 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 8 November 2026 |
|---|---|
| Posts held | 2,767 (7 August 2026 – 8 November 2026) |
| Views total | 1,973,026 |
| Reactions total | 16,140 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 8 Nov 2026, 14:08 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.
Measured directly from 228 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.
18,529 reactions across 537 posts, in 4 distinct kinds. The most used accounts for 33.4% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 6,187 | 33.4% | |
| 🔥 | 6,173 | 33.3% | |
| 😁 | 6,112 | 33.0% | |
| 👏 | 57 | 0.308% |
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 539 of the 1,000 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 18,529 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 1,000 most recent posts we hold (the sample is capped at 1,000), published 7 October 2026 to 8 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: 3 of 913 posts held from the last 30 days (0.329%) 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).
#网友投稿:柬埔寨警方已和中国公安实现数据共享,范围涵盖柬埔寨出入境记录、在柬中国人居住登记、各类实名登记信息等。 请在柬同胞们遵守当地法律法规,请勿从事任何违法犯罪活动 🔔 点击订阅缅北通缉令频道 👉 t.me/+bO3VCrsaPyU0MzI1 ☎️ 投稿爆料联系: @pige
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缅北悬赏通缉令(曝光) pinned a video
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#马来西亚资讯:移民局公布最新数据!3万2052人涉及移民违法,累计罚款9178万令吉 11月7日,马来西亚移民局公布2026年前10个月移民执法罚款数据。从1月1日至10月31日,当局针对各类移民违法行为累计征收罚款9178万令吉,涉及32,052人。 马来西亚内政部长赛夫丁纳苏申(Saifuddin Nasution Ismail)表示,在累计罚款金额中,2459名雇主涉及5004万令吉罚款,另有29,593名非法移民涉及4174万令吉罚款。 数据显示,雇主所涉及的罚款金额已经超过总罚款的一半,反映出马来西亚当局在打击非法移民问题上,也将执法重点延伸至违规聘用外籍劳工的雇主。 部长指出,雇主有责任确保所聘用的外籍员工持有合法旅行证件及工作准证。对于违反移民法律、非法聘用外籍劳工的雇主,当局将依法采取行动。 他强调,解决非法移民问题不能仅依靠罚款,还需要持续加强执法、检查及监管工作,并呼吁民众积极举报涉嫌违反移民法律…
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#群友投稿:组团骗赔付,资金盘团队骗子! 11月6号,朋友介绍一个团队在缅甸妙瓦底镇上,说是迫切想要赚钱,被骗到妙瓦底。结果开工一个月,就被缅甸军方给扫了,老板又把他们捞出来。 出来后,说自己老板没有实力,想要离开重新找公司,有950万泰铢的赔付。我想着大哥那里需要这个团队,就联系大哥了。大哥也看好他们,就安排车去接,又是调人员,又是调车。 结果去到对方发的一个指定位置,他们却不出来,需要先把赔付给他们老板,他们才能出来。 结果他们倒打一耙,说我们是中介,只是拿茶水费,在把他们卖掉。呵呵。 其他话不需要讲太多,懂的都懂。我们这个行业,一直在缩小,希望广大同行不要被所谓的资金盘团队给骗了。我把他们18个人的视频发出来,避免同行踩坑。 他们可以全部人打视频,都会配合,说想来贵公司。 草尼玛,老子能出一千多万泰铢接你们,看得上一点茶水费吗? 🔔 点击订阅缅北通缉令频道 👉 t.me/+bO3VCrsaPyU0MzI1 …
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缅北悬赏通缉令(曝光) pinned a photo
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缅北悬赏通缉令(曝光) pinned a video
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#驻马大使姚文:创造更多共赢机遇 中马关系达历史新高度 (吉隆坡8日讯)中国驻马来西亚新任大使姚文出席马中友好协会欢迎晚宴并发言。他表示,中方将依托高质量发展与高水平开放,为马来西亚等亚太国家创造更多合作共赢机遇;在两国领导人战略引领下,当前中马关系已达到历史新高。他指出,马中关系根基在民间、动力来自人民友好,肯定马中友好协会长期在促进两国人文往来上的贡献。 马中友好协会会长拿督马吉德欢迎姚文履新,称马中关系日趋成熟,双方可持续挖掘合作空间。他提出,经贸合作固然重要,人文交流、民众相互理解同样不可或缺;要传承先辈建立的友好情谊,面向青年群体,通过学生交流、实习、奖学金、技术培训、联合科研、创业赛事、文化活动、青年领导力对话等方式,持续巩固双边友好纽带。 🔔 点击订阅缅北通缉令频道 👉 t.me/+bO3VCrsaPyU0MzI1 ☎️ 投稿爆料联系: @pige
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#群友投稿:西港汇都赌场门口,两帮中国人要干架,被保安劝阻了,看样子火气挺大的。 🔔 点击订阅缅北通缉令频道 👉 t.me/+bO3VCrsaPyU0MzI1 ☎️ 投稿爆料联系: @pige
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Showing the 12 most recent of 2,767 posts we hold for @xinwen811. 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.
Named by 3 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.
Telegram’s own answer, not this register’s. When this register asks Telegram’s API what is similar to this channel, this is the list it returns, in the exact order Telegram returns it — never re-sorted by subscribers or by anything else this register measures. The relationship, and the order, are Telegram’s; we record them and date them, and make no claim of our own about which of these channels actually resemble this one.
Read from Telegram’s recommendation API, most recently 11 August 2026. Telegram holds a list like this for a small and growing share of the register — how this is measured, and why most channel pages show nothing here.
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 92 seed channels' Telegram-generated recommendation lists in total, of which the 24 where it ranks highest are shown above. 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 8 November 2026 — this entry's latest reading, not the date you are reading this.
“缅北悬赏通缉令(曝光)” (@xinwen811), 203,615 subscribers as measured 8 November 2026. Telegram Register, tgregister.com/channel/xinwen811.
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.