🇰🇭西港蓝海赌场刚刚遭警方突查,两名中国公民被捕 据说是金边的案子,指定过来抓人的,人已经抓完撤了,不过现场还是有好多中国人正陆续搬离该赌场 关注海外大事件👉 @USD1 投稿👉 @USDE

Channel
🇰🇭 柬埔寨·西港华人圈
@dashijiangg
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Posts edited after publishing · Citations · Cite this entry
53,698subscribers
+20,036 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 31,623–100,000.
Register entry
| Telegram ID | -1001236135653 |
|---|---|
| Type | Channel |
| Username | @dashijiangg |
| Description | 欢迎订阅—柬埔寨·西港华人圈 ✍️爆料投稿: 🔥广告商务合作🔥: #东南亚 #缅甸 #缅北 #柬埔寨 #菲律宾 #迪拜 #老挝 #阿富汗 #阿联酋 #马来西亚 📢每日分享东南亚/迪拜/最新BC圈动态/行业新闻/吃瓜曝光/国际资讯(让你看尽天下事,财从八方来) |
| Created | Between 1 March 2018 and 31 July 2021 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 26 October 2026 |
| Measurements held | 47 |
| Confirmed unchanged | 1 time, most recently 26 October 2026 |
| On Telegram | t.me/dashijiangg |
Topic
National news — 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 62% 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
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 26 Oct 2026, 13:49 | 53,698 | -27 |
| 25 Oct 2026, 10:58 | 53,725 | -9 |
| 24 Oct 2026, 13:36 | 53,734 | -48 |
| 23 Oct 2026, 13:26 | 53,782 | -39 |
| 22 Oct 2026, 16:56 | 53,821 | -16 |
| 21 Oct 2026, 12:41 | 53,837 | -35 |
| 20 Oct 2026, 10:47 | 53,872 | -34 |
| 19 Oct 2026, 10:39 | 53,906 | -12 |
| 18 Oct 2026, 09:07 | 53,918 | -50 |
| 17 Oct 2026, 05:57 | 53,968 | -85 |
| 16 Oct 2026, 08:16 | 54,053 | -218 |
| 15 Oct 2026, 06:19 | 54,271 | +154 |
| 14 Oct 2026, 02:47 | 54,117 | +29,793 |
| 11 Oct 2026, 17:59 | 24,324 | +17,688 |
| 4 Oct 2026, 22:22 | 6,636 | -1,094 |
| 25 Sept 2026, 09:55 | 7,730 | -1,273 |
| 17 Sept 2026, 09:59 | 9,003 | -831 |
| 13 Sept 2026, 18:39 | 9,834 | -904 |
| 11 Sept 2026, 22:01 | 10,738 | -733 |
| 9 Sept 2026, 14:37 | 11,471 | first reading |
Engagement
920 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 84 pages of Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 0.003%
- avg views ÷ 53,698 subscribers
- Avg views / post
- 1.7
- 422 posts measured
- Reaction rate
- 50.0%
- reactions ÷ views · ER floor
- Posts in window
- 422
- of 920 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 1 of 422 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 26 October 2026 |
|---|---|
| Posts held | 920 (7 August 2026 – 26 October 2026) |
| Views total | 699 |
| Reactions total | 1 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 26 Oct 2026, 21:41 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
- Photos
- ≈10,200
- Videos
- ≈2,340
- Links
- ≈1,810
Lifetime counters from Telegram’s own channel header, read 26 October 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.
- Video runtime
- 2h 32m
- Average length
- 36s
Measured directly from 253 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
1 reaction across 1 post, in 1 kind.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 1 | 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 1 of the 920 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 1 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 920 most recent posts we hold, published 7 August 2026 to 26 October 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
🇰🇭西港蓝海赌场刚刚遭警方突查,两名中国公民被捕 据说是金边的案子,指定过来抓人的,人已经抓完撤了,不过现场还是有好多中国人正陆续搬离该赌场 关注东南亚大事件投稿👉 @iphone18
#群友投稿:住在“OB”的注意了,来了好几辆警车,西港警方大半夜出动,来者不善! 关注海外大事件👉 @USD1 投稿👉 @USDE
#群友投稿:住在“OB”的注意了,来了好几辆警车,西港警方大半夜出动,来者不善! 关注东南亚大事件投稿👉 @iphone18
🇲🇾马来西亚森林城市3个月逮捕351名涉诈嫌疑人,其中325人为中国籍 马来西亚柔佛州森林城市近期接连曝出诈骗窝点。当地媒体《东方日报》10月26日报道,过去3个月,警方先后展开两轮大规模扫荡,共逮捕351名涉嫌参与诈骗活动的人员,其中325人为中国籍。 今年7月15日,柔佛州警方突袭森林城市及周边地区的32处据点,共逮捕335人,包括309名中国籍、19名印尼籍、4名缅甸籍及4名马来西亚籍人员。警方现场查获313台电脑、1557部手机、17台笔记本电脑及其他通讯设备。初步调查显示,相关团伙涉嫌通过虚假加密货币投资、爱情诈骗等方式,针对海外受害者实施诈骗。 10月初,警方再次突袭森林城市至少5个公寓单位,捣毁两个涉嫌从事虚假加密货币投资诈骗的团伙,逮捕16名中国籍男女。调查发现,部分嫌疑人涉嫌针对中国境内民众实施诈骗,所有被捕人员均未随身携带护照。 连续发生的诈骗窝点案件引发当地居民及海外业主关注。森林城市管理层此前表示…
🇲🇾马来西亚森林城市3个月逮捕351名涉诈嫌疑人,其中325人为中国籍 马来西亚柔佛州森林城市近期接连曝出诈骗窝点。当地媒体《东方日报》10月26日报道,过去3个月,警方先后展开两轮大规模扫荡,共逮捕351名涉嫌参与诈骗活动的人员,其中325人为中国籍。 今年7月15日,柔佛州警方突袭森林城市及周边地区的32处据点,共逮捕335人,包括309名中国籍、19名印尼籍、4名缅甸籍及4名马来西亚籍人员。警方现场查获313台电脑、1557部手机、17台笔记本电脑及其他通讯设备。初步调查显示,相关团伙涉嫌通过虚假加密货币投资、爱情诈骗等方式,针对海外受害者实施诈骗。 10月初,警方再次突袭森林城市至少5个公寓单位,捣毁两个涉嫌从事虚假加密货币投资诈骗的团伙,逮捕16名中国籍男女。调查发现,部分嫌疑人涉嫌针对中国境内民众实施诈骗,所有被捕人员均未随身携带护照。 连续发生的诈骗窝点案件引发当地居民及海外业主关注。森林城市管理层此前表示…
国内反诈App被指监测境外财经网站访问记录,超2亿部手机安装引发隐私争议 据相关媒体2026年10月22日报道,外媒再次关注中国国家反诈中心App的监测权限及隐私争议。相关报道援引《金融时报》此前的调查称,该应用在2021年已安装于超过2亿部手机,部分用户在访问境外财经新闻网站后,曾接到警方电话或被询问相关情况。 报道提到,一名上海用户称,自己访问美国财经新闻网站后接到警方联系,并被询问是否有海外联系人、是否经常浏览境外网站。山东一名用户则表示,访问彭博社等境外信息平台后,曾连续多日接到警方电话。 据受访者反映,该应用曾被要求获取多项手机权限,包括通话记录、短信等相关信息,引发部分用户对个人隐私及数据安全的担忧。 国家反诈中心App推出的主要目的是识别涉诈电话、短信及恶意软件。不过,相关案例也引发外界对反诈技术使用范围及个人信息保护的讨论。 关注海外大事件👉 @USD1 投稿👉 @USDE
国内反诈App被指监测境外财经网站访问记录,超2亿部手机安装引发隐私争议 据相关媒体2026年10月22日报道,外媒再次关注中国国家反诈中心App的监测权限及隐私争议。相关报道援引《金融时报》此前的调查称,该应用在2021年已安装于超过2亿部手机,部分用户在访问境外财经新闻网站后,曾接到警方电话或被询问相关情况。 报道提到,一名上海用户称,自己访问美国财经新闻网站后接到警方联系,并被询问是否有海外联系人、是否经常浏览境外网站。山东一名用户则表示,访问彭博社等境外信息平台后,曾连续多日接到警方电话。 据受访者反映,该应用曾被要求获取多项手机权限,包括通话记录、短信等相关信息,引发部分用户对个人隐私及数据安全的担忧。 国家反诈中心App推出的主要目的是识别涉诈电话、短信及恶意软件。不过,相关案例也引发外界对反诈技术使用范围及个人信息保护的讨论。 关注东南亚大事件投稿👉 @iphone18
金边警察局召开10月份工作总结会议,部署11月治安工作 10月26日上午,柬埔寨金边市警察局召开2026年10月份犯罪形势及社会治安维护工作总结会议,回顾当月执法行动成果,并部署2026年11月的重点工作。 会议由金边市警察局局长兼副国家警察总监春纳林(Chhun Narith)中将主持。出席人员包括警察局副局长、副参谋长、33个专业部门负责人、14个区警察局督察及相关官员。 会议在国家警察总监萨尔特上将的工作指导精神下举行,重点围绕当月犯罪形势、维护社会治安秩序的行动成果,以及下一阶段的工作方向进行总结和部署。 关注海外大事件👉 @USD1 投稿👉 @USDE
金边警察局召开10月份工作总结会议,部署11月治安工作 10月26日上午,柬埔寨金边市警察局召开2026年10月份犯罪形势及社会治安维护工作总结会议,回顾当月执法行动成果,并部署2026年11月的重点工作。 会议由金边市警察局局长兼副国家警察总监春纳林(Chhun Narith)中将主持。出席人员包括警察局副局长、副参谋长、33个专业部门负责人、14个区警察局督察及相关官员。 会议在国家警察总监萨尔特上将的工作指导精神下举行,重点围绕当月犯罪形势、维护社会治安秩序的行动成果,以及下一阶段的工作方向进行总结和部署。 关注东南亚大事件投稿👉 @iphone18
#网友投稿:西港中国城附近的520酒店”进行检查,目前已抓住了几个没护照的人了,附近的兄弟注意了。 此前帖子:https://t.me/usd1/55765 关注海外大事件👉 @USD1 投稿👉 @USDE
#网友投稿:西港中国城附近的520酒店”进行检查,目前已抓住了几个没护照的人了,附近的兄弟注意了。 此前帖子:https://t.me/usd1/55765 关注海外大事件👉 @USD1 投稿👉 @USDE
Showing the 12 most recent of 920 posts we hold for @dashijiangg. 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.
Posts edited after publishing
@dashijiangg edited 2 posts after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.
An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.
- First edit seen
- 15 October 2026
- Most recent edit
- 15 October 2026
Mentions
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.
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 26 October 2026 — this entry's latest reading, not the date you are reading this.
“🇰🇭 柬埔寨·西港华人圈” (@dashijiangg), 53,698 subscribers as measured 26 October 2026. Telegram Register, tgregister.com/channel/dashijiangg.
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.