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Channel
@dny2023flb
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
103,234subscribers
-251 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 100,000–316,228.
| Telegram ID | -1001834649988 |
|---|---|
| Type | Channel |
| Username | @dny2023flb |
| Description | 东南亚菲律宾曝光频道专注于东南亚华人最新动态资讯,生活故事分享,海外华人求助,让你看尽海外华人大小事。 投稿曝光: @llipook 商务合作: @llipook 本频道只负责相关发布信息,真假自行甄别 #东南亚 #菲律宾 #柬埔寨 #越南 |
| Created | Between 1 October 2022 and 31 August 2023— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 12 August 2026 |
| Measurements held | 7 |
| Confirmed unchanged | 1 time, most recently 12 August 2026 |
| On Telegram | t.me/dny2023flb |
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 10 August 2026 and assigned it the closest of 31 fixed categories, at 99% 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.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 12 Aug 2026, 05:25 | 103,234 | -43 |
| 11 Aug 2026, 02:49 | 103,277 | -58 |
| 9 Aug 2026, 23:31 | 103,335 | -110 |
| 8 Aug 2026, 23:18 | 103,445 | -22 |
| 8 Aug 2026, 01:23 | 103,467 | -18 |
| 7 Aug 2026, 18:00 | 103,485 | no change |
| 7 Aug 2026, 17:53 | 103,485 | first reading |
77 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 15 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 63 of 77 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 12 August 2026 |
|---|---|
| Posts held | 77 (7 August 2026 – 12 August 2026) |
| Views total | 183,637 |
| Reactions total | 2,424 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 12 Aug 2026, 18:31 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 12 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 19 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.
2,424 reactions across 63 posts, in 9 distinct kinds. The most used accounts for 12.7% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 😍 | 308 | 12.7% | |
| 💯 | 294 | 12.1% | |
| 👍 | 278 | 11.5% | |
| 🥰 | 277 | 11.4% | |
| 🎉 | 273 | 11.3% | |
| ❤ | 263 | 10.8% | |
| ❤🔥 | 255 | 10.5% | |
| 🤩 | 241 | 9.94% | |
| 🔥 | 235 | 9.69% |
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 63 of the 77 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 2,424reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 77 most recent posts we hold, published 7 August 2026 to 12 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.
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#柬埔寨新闻 柬埔寨9月举办国际打击电诈大会 FBI或将参加 柬埔寨将于9月23日至24日在金边主办“2026年打击网络诈骗国际会议”,旨在汇聚各国政府、国际组织及执法机构等多方力量,共同打击并切断跨国网络诈骗链条。 柬埔寨新闻部发言人强调,此次大会对于展示柬国跨国合作决心以及应对全球新型犯罪具有重要意义。总理洪玛奈此前表示,预计美国联邦调查局(FBI)及多国执法机构代表将出席会议,深化信息共享与联合执法。
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#柬埔寨资讯 木牌发生绑架案!3名越南绑匪落网! 昨天上午,柬埔寨柴桢省巴域市发生一起绑架案。接到民众报警后,警方迅速展开追捕。 面对围追堵截,3名嫌犯在途中弃置一名越南籍受害人,并弃车逃入稻田。警方包围搜查,于当天上午10时30分成功抓获3名越南籍男嫌犯,现场扣押作案车辆、3把刀具及手机等物品,受害人安全获救。 目前,案件正依法移交地方法院审理。
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#小姐姐吐槽 我的前男友,我是在柬埔寨蒙多基里园区做扶手的,在包厢认识一个做资金盘的代理叫 #宇白 第一次点我就约我去酒店开房,我没去,后面就要包养我一个月给我1万美金叫我不要上班 我那个时候还有男朋友,我男朋友也是跟他一个公司都是在大老板冬天下面做代理的,他让我分手,我考虑了很久再加上我男朋友爱赌,就分手了跟宇白在一起 刚在一起一个月的时候我下面就很痒,我刚开始以为是熬夜上火,去打了几天消毒水就好了,这样反复几个月,后面医生感觉不对让我去大医院做检查,医生问我有没有男朋友我说有,他支支吾吾不说话,我瞬间明白了 我回家就去问宇白是不是有病,他开始不承认把我骗到老挝,后面控制我承认自己有艾滋病,当时我下面红肿,他让我先回国看,到时候给我钱治病,前面一直有给,后面直接不理我 在东南亚做扶手的姐妹一定要看清这个人,做资金盘诈骗中国人一波赚了几千万,姐妹们别被他的糖衣炮弹伤害
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#菲律宾资讯 经营连锁超市的中国老板遭绑架,绑匪索要100万美元赎金,监控录像曝光 据菲媒报道,事件发生于8月2日深夜。监控画面显示,当晚11时39分50秒,受害男子正驾驶一辆黑色轿车准备倒车,一辆白色面包车突然从后方将其截停。 车上迅速冲下5名持枪劫匪,其中有人持有AK47,强行将受害者押上面包车。 11点40分15秒左右,白色面包车离开现场。从拦截到将人挟持带离,绑匪仅用了不到25秒,动作极度干练利落。 据报道,绑匪向受害者家属索要100万美元赎金,并要求以加密货币形式支付。幸运的是,8月4日,该男子趁绑匪醉酒防备松懈之际,带着手铐翻窗逃脱并成功报警。 截至本文发帖,当地警方已抓获其中3名中国籍绑匪及1名涉嫌协助租车的本地女子,尚有2名嫌犯在逃。
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#越南新闻 后江省工业区公职人员违规履职致百亿国资流失,11名涉案人员悉数获刑 2026年8月11日,越南芹苴市法院完成一审宣判,后江省工业区基建公司及工业区管委会共计11名前管理人员、职员全部被依法惩处。2014至2023年间,这群公职人员滥用职权、肆意违背财会管理制度,肆意挥霍处置国有资产,累计造成约148亿越南盾巨额经济损失,其中贪腐谋私带来损失65亿余盾,账务违规产生损失近83亿盾。主犯范明全被判八年六个月,多名骨干相继获八年上下刑期,部分涉案人员适用缓刑。涉案人员合计补缴132亿余盾赔偿金上缴国库,法院依照案情,对土地证件、钱款逐一核算退还,厘清涉案财物归属。 公职人员手握公权却肆意侵害国有资产,终究难逃法律制裁。此次集中宣判彰显越南整治公职贪腐、守护国有资产的决心,起到极强警示震慑作用。
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#柬埔寨资讯 男生11年级留级隐瞒实情惧怕家长训斥,无证混入高中毕业考场被核查查获 2026年8月11日柬埔寨反腐败局发布通报,磅湛省金边高中考点曝出违规进考场事件。学生Soun Visa在上一学年11年级考核失利遭到留级,并不具备高中毕业统考报考资格。因惧怕遭到父母斥责,他长期向家人隐瞒学业实情,谎称自己顺利升学拥有考试权限。8月10日升学统考开启当天,这名学生悄悄混入考场参与考试,很快工作人员核对考生名册时发现并无其信息。考试主管部门、反腐败工作组随即联系学生父亲到场核实情况,家长才知晓孩子留级的真相,经查不存在替考行为。工作人员对该学生进行严肃训诫,学生当着众人与家长的面作出承诺,保证今后不会再有此类弄虚作假的行为。 孩子因畏惧批评选择撒谎铤而走险,既破坏考试公平,也折射出亲子沟通存在欠缺。正视学业得失远比遮掩过错重要,家长也需多包容引导,缓解孩子心理压力。
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Showing the 12 most recent of 77 posts we hold for @dny2023flb. 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.
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 12 August 2026 — this entry's latest reading, not the date you are reading this.
“柬埔寨 菲律宾 越南 东南亚大曝光” (@dny2023flb), 103,234 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/dny2023flb.
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.