💎🎰🙌💵 😀💰💸💸 💳💳💳💳💳💳💳💳💳 💳💳💳💳💳💳💳💳💳 🧐专业服务 超高限红 毫秒出款 ❤️视讯 — 索莱尔/DB/CQ9高限红 ❤️电子 — PG/PP/CQ9 一注2000 ❤️彩票 — 独家综艺28/哈希区块彩 🏆OK游戏中心 公群9 入驻300万U 🏆新币担保 公群999 入驻100万U 官方网址 ➔ 9Y.COM 官方飞投 ➔ @GF9Y 官方唯一客服 ➔ @KF9Y 官方唯一频道 ➔ @WWW9YCOM 💎🐋🐋🐋🐋🐋🐋🐋🐋💎
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Channel
@vtttt
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Handles named that no longer answer · Cite this entry
78,188subscribers
-30,268 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 31,623–100,000.
| Telegram ID | -1001068094876 |
|---|---|
| Type | Channel |
| Username | @vtttt |
| Description | 缅甸大事件专注海外华人最新资讯 东南亚地区最新动态,海外华人求助 让你看尽海外大小事 ! ✅投稿商务: @sssi8 ✅双向联系: @vttttvipbot 缅甸二手: @YT5559 🚀联盟导航: @LYYYY 缅甸|老挝|泰国|柬埔寨|菲律宾 |马来|斯里兰卡 本频道不做任何立场声明,并鼓励友好交流 和谐环境! |
| Created | Between 1 May 2016 and 28 February 2017 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 1 September 2026 |
| Measurements held | 26 |
| Confirmed unchanged | 1 time, most recently 1 September 2026 |
| On Telegram | t.me/vtttt |
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 100% 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 |
|---|---|---|
| 1 Sept 2026, 22:27 | 78,188 | -52 |
| 1 Sept 2026, 01:47 | 78,240 | -185 |
| 30 Aug 2026, 23:18 | 78,425 | -152 |
| 29 Aug 2026, 23:42 | 78,577 | -123 |
| 29 Aug 2026, 00:08 | 78,700 | -119 |
| 27 Aug 2026, 22:38 | 78,819 | -77 |
| 27 Aug 2026, 01:47 | 78,896 | -60 |
| 25 Aug 2026, 23:06 | 78,956 | -106 |
| 24 Aug 2026, 22:03 | 79,062 | -205 |
| 23 Aug 2026, 10:46 | 79,267 | -158 |
| 22 Aug 2026, 00:59 | 79,425 | -1,960 |
| 20 Aug 2026, 16:05 | 81,385 | -361 |
| 19 Aug 2026, 17:38 | 81,746 | -165 |
| 18 Aug 2026, 15:38 | 81,911 | -101 |
| 17 Aug 2026, 14:07 | 82,012 | -162 |
| 16 Aug 2026, 06:25 | 82,174 | -2,341 |
| 14 Aug 2026, 18:15 | 84,515 | -84 |
| 13 Aug 2026, 08:36 | 84,599 | -139 |
| 12 Aug 2026, 11:23 | 84,738 | -16,876 |
| 11 Aug 2026, 08:14 | 101,614 | first reading |
634 posts held, back to 6 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 57 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 466 of 634 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 1 September 2026 |
|---|---|
| Posts held | 634 (6 August 2026 – 1 September 2026) |
| Views total | 2,607,433 |
| Reactions total | 31,047 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 2 Sept 2026, 03:05 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 2 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.
Measured directly from 160 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.
31,047 reactions across 466 posts, in 12 distinct kinds. The most used accounts for 11.3% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 3,493 | 11.3% | |
| 💯 | 3,485 | 11.2% | |
| 🥰 | 3,473 | 11.2% | |
| ❤🔥 | 3,457 | 11.1% | |
| 🤩 | 3,454 | 11.1% | |
| 👍 | 3,434 | 11.1% | |
| 🔥 | 3,421 | 11.0% | |
| 🎉 | 3,415 | 11.0% | |
| 😍 | 3,353 | 10.8% | |
| 😁 | 27 | 0.087% | |
| ⚡ | 19 | 0.061% | |
| 👏 | 16 | 0.052% |
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 466 of the 634 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 31,047 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 634 most recent posts we hold, published 6 August 2026 to 1 September 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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#网友投稿:这个人借钱不还 他人籍贯 #老街 现在 #勐拉 家住山上 6月份给他借钱 现在叫他还钱 说要给我转微信 直接把我拉黑了! 🤣 缅甸大事件: @VTTTT 投稿: @sssi8
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今日凌晨勃固省东吁市发生油罐车爆炸事故! 据初步消息,今天(9月1日)凌晨6时许,勃固省东吁市宝道穆佛塔附近的公路旁,一辆油罐车发生爆炸。 据悉,事故系一辆拖挂车与油罐车相撞,导致油罐车爆炸起火。 🤣 缅甸大事件: @VTTTT 投稿: @sssi8
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曼德勒街头暴力事件:因挪车口角,普拉多狂碾4辆摩托车后逃逸 缅甸曼德勒市近日发生一起恶劣事件。起因是军方车辆司机要求路边车主挪开摩托车,因一旁路人开玩笑回怼“不给挪”,激怒了普拉多(Prado)司机。 随后,该司机驾车发怒冲撞,直接碾压路边停放的4辆摩托车,其中1辆被卡在车底,一路火花带闪电地被拖行。事发后,涉事车辆并未停车,而是带着被卡住的摩托车直接逃离现场。目前事件原因仍在调查中。 🤣 缅甸大事件: @VTTTT 投稿: @sssi8
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马莱镇12名军方附属人员遭袭身亡 8月31日清晨6时许,曼德勒省马莱镇坦马基村,军方任命的村长、骠绍梯组织领导人梭林泰及11名成员在村中开会时,遭反抗武装“马莱卫士”袭击,12人当场死亡。 “马莱卫士”称,死者均为军方组建的民团成员,属合法军事目标;军方则称死者是村长和普通平民。双方说法截然不同。当地民众高度关注此事。 🤣 缅甸大事件: @VTTTT 投稿: @sssi8
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TG创始人发文:Telegram钱包即将到来! Telegram 中的 Gram 钱包已准备就绪,目前可供部分用户访问。 我们将在未来几周内,逐步向我们的十亿以上用户推出该功能。 感谢批准驱动该钱包的智能合约的验证者,未来钱包的升级将无需进行痛苦的迁移。 这只是我们构建的创新之一,旨在让非托管钱包变得可用 ✨ 🤣 缅甸大事件: @VTTTT 投稿: @sssi8
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仰光一犬遭宰食案:5名男子被判监禁及罚款 在仰光省玛仰贡镇区,一名女子声称,因涉及宰杀并食用一只狗,包括宰杀者、销售者以及买卖中介在内的5名男子,已被镇区法院判处监禁和罚款。这名提起诉讼的女子莫诺温敏告诉BBC。 她说:“这只狗并非因为咬人或挑衅而被杀,而是因为想吃狗肉才被宰杀,这种情况无论如何都无法接受 🤣 缅甸大事件: @VTTTT 投稿: @sssi8
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Showing the 12 most recent of 634 posts we hold for @vtttt. 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 — 761,978 of 1,629,535 entries 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.
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.
@vtttt named 2 handles that resolve to nothing today. That is a fact about the reference, not necessarily a fact about the handle’s history — see the two groups below.
Most of these may never have existed as a live channel at all. A handle a channel names can be a typo, an aspirational name nobody registered, or a channel that was already gone before this one ever mentioned it. Unless a row below is marked evidenced, all we know is that it references a handle that is not a live channel today — not that anything “died”. How this is measured.
We ourselves saw each of these resolve to a real page at some point before it went vacant — a genuine, evidenced change, not an inference from absence.
References a handle that is not a live channel — we have no record it ever was one.
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 1 September 2026 — this entry's latest reading, not the date you are reading this.
“缅甸大事件|@VTTTT” (@vtttt), 78,188 subscribers as measured 1 September 2026. Telegram Register, tgregister.com/channel/vtttt.
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.