Channel
@juenl121
On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
7,974subscribers
-50 since we began measuring on 10 August 2026
Risers and fallers across the register · movement among entries of 3,162–10,000.
| Telegram ID | -1003541608775 |
|---|---|
| Type | Channel |
| Username | @juenl121 |
| Description | 缅甸 | 亚太 | 柬埔寨 |妙瓦底 |木姐|大气力| 菲律宾。为您播报缅甸东南亚各地新闻 投稿 白天： @muning05 投稿 晚上： @qingshan173 广告 合作： @muning05 文案 馆群： @hdufie123 文字 花园： @juenweid2 闲聊 群号：https://t.me/xinwenpin 🏃♀️投稿问题：悬赏类 需要付费确保真实性避免出现恶意悬赏不回复消息情况❗️ ❌ 禁止打广告、黄、毒、发现一律T掉，本频道仅此一个，其它都是模仿！ |
| Created | Between 1 December 2025 and 31 May 2026— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 10 August 2026 |
| Last confirmed live | 17 August 2026 |
| Measurements held | 4 |
| Confirmed unchanged | 1 time, most recently 17 August 2026 |
| On Telegram | t.me/juenl121 |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 17 Aug 2026, 17:07 | 7,974 | +79 |
| 14 Aug 2026, 18:36 | 7,895 | -87 |
| 11 Aug 2026, 04:47 | 7,982 | -42 |
| 10 Aug 2026, 19:02 | 8,024 | first reading |
53 posts held, back to 10 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 6 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.
| Window | Rolling 30 days · latest post in window 20 August 2026 |
|---|---|
| Posts held | 53 (10 August 2026 – 20 August 2026) |
| Views total | 43,474 |
| Reactions total | 212 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 20 Aug 2026, 09:18 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 20 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 13 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.
212 reactions across 53 posts, in 3 distinct kinds. The most used accounts for 50.0% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 106 | 50.0% | |
| 👍 | 104 | 49.1% | |
| 🥰 | 2 | 0.943% |
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 53 of the 53 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 212reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 53 most recent posts we hold, published 10 August 2026 to 20 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.
#安全提醒：16个恶意RubyGems包伪装热门依赖，专偷钱包助记词和Telegram数据 网络安全研究人员近日发现一批伪装成热门Ruby依赖库的恶意RubyGems软件包，共涉及16个包名。攻击者故意使用与正常依赖库十分相似的拼写，诱导开发者在输入错误名称后下载安装。 这批恶意包主要模仿bundler、i18n、rake和activesupport等常用Ruby依赖。研究人员于8月15日发现相关攻击活动，并将其命名为“StubMaker”。 用户一旦安装这些恶意包，隐藏其中的代码就会在安装过程中自动运行，主要针对Windows设备。恶意程序可窃取Chrome、Edge、Brave、Opera等浏览器中保存的账号密码、Cookie和登录会话等数据，同时搜集多种加密钱包资料，并扫描钱包助记词和恢复短语。 此外，恶意程序还会读取Telegram Desktop本地数据，并收集受感染电脑的系统信息。窃取到的数据随后会被打包上传…
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#网友投稿 有那么一群人 上班聊会天没关系 但别开始上班就讲话到下班 办公室环境就那么大 全是你们声音 耳机带着都能听见你们聊那些乱七八糟 投诉也不少了了吧 开会领导点你们 跟听不懂中文一样 群里发公告点你们呢 还去群里发表情包 你们生出来的时候是不是 ချက်ကြိုး နဲ ရှက်ကြိုးမှားဖြတ် ~~~~~~~~~~~~~~~~~~~~~~~~~ 🔔 订阅亚太新闻频道 ↓ 🔗 https://t.me/juenl121 ☎️ 欢迎爆料： @muning05
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#网友投稿 🇱🇦老挝金三角特外新村市场对面现在有50多个老挝警察在查，还在特外的都小心点 ~~~~~~~~~~~~~~~~~~~~~~~~~ 🔔 订阅亚太新闻频道 ↓ 🔗 https://t.me/juenl121 ☎️ 欢迎爆料： @muning05
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#缅英爆料 兄弟们，让我给你们带来一些好消息和有趣的事情 她是个非常邪恶的人，兄弟们，如果你们看到她，一定要避开她 但如果你想和她发生性关系，只需1000/2000 泰铢，你就可以和她以各种方式发生性关系 她与之前分手的前男友重燃旧情，仍然想要性，并且不断向他要钱 而和她分手的那个中国男人，现在正和一个可爱的女孩谈恋爱，那是我朋友 他想破坏别人的新感情，性行为毫无尊重，而且每天都要钱，现在，由于她的骚扰，我的朋友正在遭受痛苦，不得不住院接受药物治疗。 她是一位来自缅甸北部地区的亚洲女性。莫科特人都是这样的吗？哈哈 那个女孩很有钱，总是跟每个男人都上床 中国富人把她视作自己的长子。我想问，她现在的男朋友真的不知道她和别人有染，还用钱欺骗她吗？ 或者，她的中国男友很穷，付不起你高额的性交易费用，所以他才会在与其他女性的关系中骚扰你，并以欺诈手段向你索要钱财？很搞笑她不过是个妓女 连当妓女都不如的女孩真令人作呕 ~~~~~~…
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🇰🇭一年关闭605个诈骗窝点，4147名嫌疑人被移送法院 柬埔寨政府过去一年持续打击跨境网络诈骗，共调查751处涉嫌诈骗地点，并关闭605个诈骗窝点 当局还检查了195家赌场，其中20家因涉嫌与诈骗活动有关被吊销执照，29家被暂停营业。 此次行动共驱逐来自38个国家的21,666名外国人，并将4147名涉案嫌疑人移送法院 柬埔寨政府表示将以“零容忍、无例外、不退缩”的政策持续打击网络诈骗犯罪。 柬埔寨还计划于9月23日至24日在金边举办ICCOS-2026国际网络诈骗打击大会，多国执法机构及国际组织将参与。 ~~~~~~~~~~~~~~~~~~~~~~~~~~ 🔔 订阅亚太新闻频道 ↓ 🔗 https://t.me/juenl121 ☎️ 欢迎爆料： @muning05
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#网友曝光 此人线上伪装预约办理护照等业务骗取钱财，被骗金额1100000+250000=1350000缅币 我是在铺子给他转账的 所以没有她的账户信息，如果有人认识此人 或者给他账户提供过转账有转账电话号码的，请给提供一下 信息正确后报酬100w缅币，联系电话；09691233092飞机；dujinzhi110 ~~~~~~~~~~~~~~~~~~~~~~~~~ 🔔 订阅亚太新闻频道 ↓ 🔗 https://t.me/juenl121 ☎️ 欢迎爆料： @muning05
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#网友投稿 金贝3后面刚刚几十个人去抓五六个人，还开了几枪，具体什么情况暂时不清楚，感觉是抓DU犯 ☎️ ~~~~~~~~~~~~~~~~~~~~~~~~~ 🔔 订阅亚太新闻频道 ↓ 🔗 https://t.me/juenl121 ☎️ 欢迎爆料： @muning05
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#柬埔寨资讯：金边一女子持刀刺死男友后被警方逮捕 今天凌晨5时30分许，金边市森速区一出租屋内发生一起命案。一名女子在房间内持刀刺死其男友，引发周边居民震惊。 案发后，当地警方联合金边市警察局刑事法医与科学技术部门迅速赶赴现场勘查。目前，涉案女子已被警方当场逮捕，正面临依法起诉。 PS：七夕到处命案频发，渡劫日？ ~~~~~~~~~~~~~~~~~~~~~~~~~ 🔔 订阅亚太新闻频道 ↓ 🔗 https://t.me/juenl121 ☎️ 欢迎爆料： @muning05
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#4名中国公民偷渡泰国被捕 疑欲转移电诈基地至缅甸 8月18日，泰国廊开府警方逮捕4名从老挝偷渡入境的中国籍男子（22-26岁）及1名泰国司机，查获电脑、网络设备及大量手机，4人均无护照。 泰国司机供述，#其接应4人渡河后计划送往缅甸，每人运费6000泰铢。警方初步研判，该团伙疑为躲避老挝打击，拟将诈骗基地迁至缅甸。 4人否认与查获设备有关，案件正进一步调查中。 ~~~~~~~~~~~~~~~~~~~~~~~~~ 🔔 订阅亚太新闻频道 ↓ 🔗 https://t.me/juenl121 ☎️ 欢迎爆料： @muning05
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#木姐约600名电诈人员转移后在南帕嘎、贵慨一带隐匿 8月19日，缅甸掸邦北部木姐镇区莫东村组一带转出的数百名网络诈骗人员，在前往南帕嘎和贵慨一带后分散隐匿。 当地知情人士透露，这批人员约有600人，此前于8月11日转移至木姐莫东村附近，之后再次分散转移。 其中一部分人前往南坎19村一带，一部分转往棒赛，还有人去了南帕嘎，另有一批人进入贵慨附近的一处养牛场。 转移过程中，这些人员多次改变对外透露的去向，一会儿称要前往这个方向，一会儿又改称去其他地方。目前，一批人员已经聚集在贵慨附近的养牛场，并受到武装人员保护 当地获得的信息还提到，此次转移由掸邦进步党（SSPP）安排，缅甸民族民主同盟军（MNDAA）也有参与。此前，木姐部分网络诈骗公司已陆续向莫东村组一带转移，随后相关人员又进一步分散至周边地区 ~~~~~~~~~~~~~~~~~~~~~~~~~ 🔔 订阅亚太新闻频道 ↓ 🔗 https://t.me/juenl12…
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#网友曝光 这个男的叫阿浪，中国湖北的。他们公司在缅甸三佛塔，公司在缅甸KTV后面三号院。 他这个人在三佛塔一直在骗他国内的兄弟过来，把人家骗说都是自己的兄弟，做事不会打人，把人家骗到三佛塔然后他们开不出业绩、开不出单就给人家打得生不如死、天天打。如果他给他们的机会他们做不出来，就把人家卖出去。 还有，他以前谈过缅甸女朋友，他们吵架，那个缅甸女孩子就跟他要10万泰铢，他不给，那个女的已经跟他说不给就算了，然后他们已经分手了。 他们的兄弟车钥匙不见了，就一直说那个女的拿，那个女的说没有：“不是我的东西拿干嘛？”那个女孩子本来就没有拿他，他就和他兄弟一起说那个女孩子，然后他就去吸毒，就打他那个缅甸女孩子。 在东南亚的女孩子看到这个男的请远离，一开始会假装对你很好，后面就会打你，也正常骗人、买卖人这个狗男人。希望能早点把他抓到送回国去，不要让他在这恶心东南亚。 ~~~~~~~~~~~~~~~~~~~~~~~~~ 🔔 订阅亚太…
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#突发❗️❗️据初布消息，中国汉奸狗腿子、果敢MNDAA将从德昂TNLA手中夺取的（贵概）辖区内的一处牛场内，接容并为从木姐逃来的数百名电诈（园区）人员提供安全保护。 Breaking❗️❗️ တရုတ်လက်ပါးစေအဖွဲကိုးကန့်MNDAAက တအောင်းTNLA ဆီကနေသိမ်းယူထားတဲ့ ကွတ်ခိုင်နယ်ထဲကနွားခြံထဲမှာ မူဆယ်ကနေထွက်ပြေးလာတဲ့ကျားဖြန့်ရာနဲ့ချီလက်ခံလုံခြုံရေးပေးထားတယ်လို ကနဦးသိရတယ်။ 免责声明：素材来源于网友匿名投稿，未对内容真实性进行核验，本频道仅作分享，不代表任何立场。 ~~~~~~~~~~~~~~~~~~~~~~~~~ 🔔 订阅亚太新闻频道 ↓ 🔗 https://t.me/juenl121 ☎️ 欢迎爆料： @muning05
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Showing the 12 most recent of 53 posts we hold for @juenl121. 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 — 1,293,839 of 1,566,395entries 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 1 registered channel — 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.
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 17 August 2026 — this entry's latest reading, not the date you are reading this.
“柬埔寨新闻｜东南亚新闻｜缅甸亚太新闻准时为您播报缅甸东南亚各地新闻” (@juenl121), 7,974 subscribers as measured 17 August 2026. Telegram Register, tgregister.com/channel/juenl121.
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.