柬埔寨新币曝光|新闻大事件 pinned a photo

Channel
柬埔寨新币曝光|新闻大事件
@jianpuzhai_xinbibaoguang
On this record: Topic · Growth · Engagement · What this channel posts · Posts · Citations · Cite this entry
64,022subscribers
-5,454 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 | -1001387140967 |
|---|---|
| Type | Channel |
| Username | @jianpuzhai_xinbibaoguang |
| Description | 🔴投稿/曝光: @Xinbi_baoguang 东南亚新币曝光 @dongnanya_xinbibaoguang 菲律宾新币曝光 @feilvbin_xinbibaoguang 柬埔寨新币曝光 @jianpuzhai_xinbibaoguang 泰国新币曝光 @taiguo_xinbibaoguang 缅甸老挝新币曝光 @miandian_laowo_xinbibaoguang 迪拜新币曝光 @dubai_xinbibaoguang |
| Created | Between 1 March 2018 and 31 August 2021 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 25 September 2026 |
| Measurements held | 33 |
| Confirmed unchanged | 1 time, most recently 25 September 2026 |
| On Telegram | t.me/jianpuzhai_xinbibaoguang |
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 9 September 2026 and assigned it the closest of 31 fixed categories, at 81% 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 |
|---|---|---|
| 25 Sept 2026, 18:18 | 64,022 | -501 |
| 19 Sept 2026, 05:19 | 64,523 | -138 |
| 16 Sept 2026, 17:17 | 64,661 | -89 |
| 14 Sept 2026, 18:22 | 64,750 | -118 |
| 13 Sept 2026, 04:20 | 64,868 | -204 |
| 11 Sept 2026, 09:42 | 65,072 | -741 |
| 8 Sept 2026, 18:37 | 65,813 | -424 |
| 5 Sept 2026, 10:20 | 66,237 | -189 |
| 3 Sept 2026, 16:42 | 66,426 | -203 |
| 2 Sept 2026, 07:43 | 66,629 | -141 |
| 1 Sept 2026, 06:37 | 66,770 | -74 |
| 31 Aug 2026, 08:57 | 66,844 | -125 |
| 30 Aug 2026, 08:12 | 66,969 | -99 |
| 29 Aug 2026, 09:33 | 67,068 | -73 |
| 28 Aug 2026, 07:44 | 67,141 | -59 |
| 27 Aug 2026, 08:23 | 67,200 | -78 |
| 26 Aug 2026, 06:32 | 67,278 | -123 |
| 25 Aug 2026, 03:43 | 67,401 | -157 |
| 23 Aug 2026, 23:34 | 67,558 | -232 |
| 22 Aug 2026, 09:56 | 67,790 | first reading |
Engagement
1,079 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 107 pages of Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 4.07%
- avg views ÷ 64,022 subscribers
- Avg views / post
- 2,610
- 524 posts measured
- Reaction rate
- —
- this channel exposes no reaction counts
- Posts in window
- 628
- of 1,079 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.
| Window | Rolling 30 days · latest post in window 29 September 2026 |
|---|---|
| Posts held | 1,079 (7 August 2026 – 29 September 2026) |
| Views total | 1,367,008 |
| Reactions total | — |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 29 Sept 2026, 03:25 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
- ≈24,600
- Videos
- ≈4,150
- Links
- ≈695
Lifetime counters from Telegram’s own channel header, read 29 September 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
- 1h 21m
- Average length
- 28s
Measured directly from 177 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.
Recent posts
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柬埔寨新币曝光|新闻大事件 pinned a photo
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#全网曝光 #柬埔寨 #避坑 #避雷 #白眼狼 #黑龙江 #兔子(真名苏晓慧) #大圣 或者猴子(真名张语林) #啊强(于海伟) 黑龙江省五大连池人士 联系我,把事情最小化处理,等我找到人了,那就不那么简单处理了,还有正在找人调你们全家户籍信息,等后续带曝光
柬埔寨新币曝光|新闻大事件 pinned a video
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#网友投稿:想必大家对西港的“金贝3”都有所耳闻。 从当初号称上千人的集团,到经历柬埔寨扫荡、一次次搬家,再到停工整顿半年,如今又搬到了伊斯兰堡。 而我,作为曾经公司的管理人员,在这里兢兢业业这么多年,该做的做了,该扛的扛了,该熬的夜也熬了。可如今,因为一些所谓的“小事”让我离开,我无话可说。 不是因为我认同,而是这么多年过去,我终于明白了:一个让人拼尽全力付出,却最终连留下来的念头都没有的地方,到底是谁出了问题? 公司天天喊着“以人为本”,给自己贴“正规公司”的标签。可真正落到下面呢? 业务员、组长、主管,各个层级的点位说砍就砍,甚至拦腰砍一半。公司受到外部环境影响,要压缩成本,我理解。但既然要学正规公司,那就把正规公司的样子做出来。 天天讲绩效,实际上就是变着方法压员工工资;天天讲规矩,却不讲员工最基本的休息。既然是正规公司,为什么不能朝九晚五?为什么来了几个月,所谓周末休息有时候只剩两三个小时? 人是出来赚钱…
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#网友投稿:西港“星汇3-1” 目前有警察正在开展执法行动 带防弹衣了,应该是抓人的,注意待在房间,别影响执法!
柬埔寨西港诈骗头目王俊万丽珍 此致:四川省自贡市公安局反诈中心。 本人实名举报:四川省自贡市富顺县人,外号大军,真名王俊。四川省自贡市人万丽珍,大家叫她阿珍、珍姐。 这两人从18年到西港,一开始搞赌博游戏机。后面遇到严打,就靠同乡万丽珍介绍帮忙,转去做电信诈骗。手下几十个人,大多数是老家人。最初在中国城金水物业,带着家里来帮衬的兄弟做国内刷单诈骗,一年多将近两年,从几个人搞到几十个。这段时间所有人加起来差不多做了2到3亿人民币的业绩。 后来又通过相好万丽珍认识其他大佬,调了一大批人去做印度股转。马上快三年了,也做了不少,差不多3到5亿人民币,涉案金额巨大。现在柬埔寨西港局势不稳,他们又带着一些老家和其他人跑到土耳其继续搞电信诈骗。 现在实名举报王俊和万丽珍,希望四川省厅、自贡市局反诈中心重点盯着这两人,立案侦查。这两人在老家富顺县,当地警务人员对他们王法宽裕,他们还是老家某某反诈的线人。也提醒同行和给他们撑腰的老板,千…
Showing the 12 most recent of 1,079 posts we hold for @jianpuzhai_xinbibaoguang. 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.
Mentions
Named by 6 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.
@feilvbin_xinbibaoguang · 64,57716 posts迪拜新币曝光|新闻大事件
@dubai_xinbibaoguang · 64,47014 posts泰国新币曝光|新闻大事件
@taiguo_xinbibaoguang · 64,13513 posts缅甸老挝新币曝光|新闻大事件
@miandian_laowo_xinbibaoguang · 64,79412 posts东南亚新币曝光|新闻大事件
@dongnanya_xinbibaoguang · 85,30011 posts新币曝光总站
@xinbibaoguangzongzhan · 2,3971 post
Names
Channels on the register whose handles appear in this channel's posts.
@ty000 · 30045 posts78.COM-官方频道@DF78
@tg78com · 19,99236 posts东南亚新币曝光|新闻大事件
@dongnanya_xinbibaoguang · 85,30012 posts迪拜新币曝光|新闻大事件
@dubai_xinbibaoguang · 64,47012 posts菲律宾新币曝光|新闻大事件
@feilvbin_xinbibaoguang · 64,57712 posts缅甸老挝新币曝光|新闻大事件
@miandian_laowo_xinbibaoguang · 64,79412 posts泰国新币曝光|新闻大事件
@taiguo_xinbibaoguang · 64,13512 posts新币曝光总站
@xinbibaoguangzongzhan · 2,39712 posts8K国际官方频道
@PG8K001 · 5876 posts华人资讯|🍉吃瓜群众
@chigua_huaren_chigua · 4,9881 post华人资讯【求职&招聘】
@Huaren_zhaopin_qiuzhi · 1,1771 post华人资讯导航频道
@HuarenZM · 3,3181 postPG仔·通知频道
@nft_Market_user · 2,8291 post8G.com
@tg8g · 32,5981 post
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 25 September 2026 — this entry's latest reading, not the date you are reading this.
“柬埔寨新币曝光|新闻大事件” (@jianpuzhai_xinbibaoguang), 64,022 subscribers as measured 25 September 2026. Telegram Register, tgregister.com/channel/jianpuzhai_xinbibaoguang.
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.