Channel
@dongnanya_xinbibaoguang
On this record: Topic · Observations · Also posting the same content · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
89,202subscribers
-1,019 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 31,623–100,000.
| Telegram ID | -1001279404963 |
|---|---|
| Type | Channel |
| Username | @dongnanya_xinbibaoguang |
| Created | Between 1 April 2018 and 30 June 2021— 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/dongnanya_xinbibaoguang |
Other / unclassifiable — 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 75% 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.
These are measurements, not verdicts. Each one below states something we counted, alongside the evidence it was counted from, so you can check it rather than take it. None of them is graded: every observation this register holds is recorded at severity 0, because the precision of the detectors behind them has not been measured yet, and a rating we cannot support is worse than none. Read each as a fact about the data, not as a judgement about the channel. How we measure.
Posts published here appear word for word on 2 other registered channels. The matching is on the text itself, not on Telegram’s forward marker, so it finds a copy whether or not it was labelled as one.
| Posted first | Then | Overlap | Gap |
|---|---|---|---|
| @Banma_xinwen/1076777 Aug 2026, 11:10 UTC | @dongnanya_xinbibaoguang/34415 · this entry7 Aug 2026, 11:10 UTC | 1.00 | under a minute |
| @Banma_xinwen/1076787 Aug 2026, 13:15 UTC | @dongnanya_xinbibaoguang/34416 · this entry7 Aug 2026, 13:15 UTC | 1.00 | under a minute |
| @Banma_xinwen/1076847 Aug 2026, 13:18 UTC | @dongnanya_xinbibaoguang/34422 · this entry7 Aug 2026, 13:18 UTC | 1.00 | under a minute |
| @Banma_xinwen/1076857 Aug 2026, 13:21 UTC | @dongnanya_xinbibaoguang/34423 · this entry7 Aug 2026, 13:21 UTC | 1.00 | under a minute |
| @Banma_xinwen/1076907 Aug 2026, 14:41 UTC | @dongnanya_xinbibaoguang/34426 · this entry7 Aug 2026, 14:41 UTC | 1.00 | under a minute |
| @dongnanya_xinbibaoguang/34415 · this entry7 Aug 2026, 11:10 UTC | @fw99244/151277 Aug 2026, 11:11 UTC | 1.00 | under a minute |
| Channel | Matching posts | Text overlap | Typical gap | Published first |
|---|---|---|---|---|
| @Banma_xinwen | 6 (5/6 hand-verifiable sample passed) | 1.00 | under a minute | this entry (6–0) |
| @fw99244 | 6 (5/6 hand-verifiable sample passed) | 1.00 | under a minute | this entry (6–0) |
Text overlap is the Jaccard coefficient over the set of distinct three-word phrases in the two bodies: 1.00 is identical wording, and the threshold for counting a pair at all is 0.70. Candidates are generated by simhash LSH (4 x 16-bit bands, exact Hamming <= 3) verified against the bodies with Jaccard over the SET of distinct 3-word shingles. Published first counts which side of each matching pair carries the earlier timestamp — in this corpus, which is the limitation directly below.
What this cannot establish
MEASURED, DOMINANT ERROR SOURCE: a post ingested before 2026-08-06 may have carried a forward header that was not recorded. A 45-pair hand-check against live t.me pages found 14 (31%) where the live page shows a forward header naming the other channel and the database has none, plus 4 more (9%) naming a third party. The text match itself was wrong 0 times out of 45. Read attribution_capture.items_in_trusted_window before treating the unattributed count as a claim.
Telegram lets a channel forward a post with a header naming the source, and we only began reliably recording that header on 2026-08-06. None of the 0 matches recorded here fall after that date, so for this entry we cannot say whether any of them carried a credit. The duplication is measured; the absence of attribution is not.
“Published first” means first in this corpus. We hold 9 comparable posts for this entry, running 7 August 2026 to 8 August 2026. A channel we have read one page deep will look younger than a neighbour we have read in full, and the order would flip with no change in the underlying facts.
The detector’s own notes on this observation, as it recorded them. Names in this_style are fields of the underlying evidence record, which the plain-English paragraphs above read out for this entry.
Across the whole group of 3, the earliest publisher we hold is @Banma_xinwen. That is a statement about our reading window, not a claim of authorship.
Recorded under the key clone_source, last confirmed 8 August 2026. An observation that a later pass no longer finds is cleared, and a cleared observation is removed from this page rather than being shown struck through — we do not keep publishing a claim we have withdrawn. Dispute an observation.
This channel’s posts match, word for word or near enough, posts on 2 other registered channels, found by comparing text fingerprints across every channel on the register. That matching has been checked by hand against the live Telegram pages and found reliable — 0 wrong of 45 pairs re-read.
Which channel, if either, published first is deliberately not shown. The same hand-check found that reading wrong 18 of 45 times — 60%, no better than a coin flip — because it depends on how deep our own crawl happened to reach into each channel’s history, not on when the content was actually first posted. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Word-for-word matching has several ordinary explanations besides copying — a channel mirroring itself, an unattributed repost, or two channels independently repeating the same wire story — and this measurement cannot tell those apart. How this is measured.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 12 Aug 2026, 22:44 | 89,202 | -204 |
| 11 Aug 2026, 22:54 | 89,406 | -183 |
| 10 Aug 2026, 21:38 | 89,589 | -234 |
| 9 Aug 2026, 19:21 | 89,823 | -232 |
| 8 Aug 2026, 16:15 | 90,055 | -166 |
| 7 Aug 2026, 19:15 | 90,221 | no change |
| 7 Aug 2026, 19:07 | 90,221 | first reading |
142 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 30 of 142 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 | 142 (7 August 2026 – 12 August 2026) |
| Views total | 276,980 |
| Reactions total | 31 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 12 Aug 2026, 18:42 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.
Measured directly from 30 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 reactions across 30 posts, in 8 distinct kinds. The most used accounts for 25.8% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 😁 | 8 | 25.8% | |
| ❤ | 5 | 16.1% | |
| 🥰 | 5 | 16.1% | |
| 🔥 | 4 | 12.9% | |
| 🎉 | 3 | 9.68% | |
| 👏 | 3 | 9.68% | |
| 🤩 | 2 | 6.45% | |
| 👍 | 1 | 3.23% |
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 30 of the 142 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 31reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 142 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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高脚苏总骗出国索高额赔付 高脚苏总，福建安溪人，安排路线把我从国内弄到柬埔寨绿巨人园区。他朋友的公司做精聊，我在国内就明确说了不做，他还多次用高薪忽悠我出国。 到了绿巨人园区后干了一个月，我说不做了想回国，对方就要高额赔付。没办法，只好安稳干了七个月。后来公司说要搬去七星海，我没去，两个月工资也没发。 高脚又让我去中国城金水园区9栋3楼333办公室做法国刷单，说工资会补。结果在那边又干了一个月，我说工资不要了，就要回国。他联合主管阿木一起给我算了1.6万赔付。我当时威胁报警，他说报警也没用，给钱才能走。最后找朋友给了他1万U，才放我出园区。 跟我一起从国内出来的兄弟一直跟着他干，我没要代理费也没要介绍费。兄弟辛辛苦苦跟了一年多，公司搬去波贝后他还继续跟着。结果波贝大检查，公司解散，高脚直接不管死活，也不安排回国。现在这货自己都回国了，压根不管下面人。 我现在只想要回那1万U赔付钱。三天内联系我，不给的话后续继续曝光。
在东南亚混久了，人都废了。不是赚钱的问题，是脑子出了问题。 以前在国内，花100块都得掂量掂量。到了这边，100美金刷出去眼睛都不眨一下。不是因为你赚得多了，是因为你把美金当冥币花了——数字小，没感觉，花完拉倒。 月底一看账单：“卧槽，这钱是我花的？”不是你是谁？鬼帮你花的？ 你以为自己在过好日子，其实就是在给东南亚打工。会所、酒吧、请客吃饭，样样不落。回国一看银行卡，余额还没你脸皮厚。 兄弟，你在国内省吃俭用，攒三万块能活半年。在那边大手大脚，三万美金只够买几个月的“面子”。面子有了，钱没了，人老了，啥也没剩下。 更蠢的是啥？你觉得这种生活正常。没存款正常，月底吃土正常，借钱发工资也正常。你管这叫“活在当下”，其实就是被这边的节奏带沟里了。 一句话：你是来赚钱的，不是来过瘾的。钱是挣来的，也是守住的。守不住，赚再多都是过路财神。别等到回国那天，才发现自己在国外潇洒了几年，实际上是在给别人的好日子买单。
#缅甸亚太买人狗高额索赔 这个买人的狗东西，在亚太做人事招聘。我介绍一个朋友进去上班，才干了十天就受不了体罚和高压，提出辞职。 对方公司居然要高额赔付，6060U加69600人民币，进的时候可是零赔付。大家记住这个狗人事，账号xz168168、awei168168111。 之前在亚太村外，现在人又被买到将军山去了。这种货大家千万别碰。
#菲律宾 #鸿运 #十一 #偷吃回扣 先给你留点做人的尊严，敏感信息先打码。今天不想把事做绝，你自己清楚走支付通道时干了哪些偷鸡摸狗的事。 你公司人好像叫你十一。我不管你在鸿运偷吃了多少商户回扣，找车队跑那些分公司不知道的业务，你干的缺德事自己心里有数。阿飞不知道、小六不知道、新一不知道，你当所有人都傻？国内有车有房的人，跑来干这种下三滥的事？从园区到马卡提，你还算个人吗？表面装人样，钱包里动了多少手脚你自己清楚。 话说到这你也能猜个八九不离十了。你问我为啥爆你？吃公司的我不管，吃相难看是你自己的事，但不守信用丢鸿运的脸，还威胁到我的利益，玩女人玩到我头上了，操你妈的！ 当初和土豆、飞机CJ_tianyue在钱包账户里搞小动作的事，你以为我不知道 有房有车，在菲还搞个小三，你可以的，巴适得很。你大概知道我是谁了，大家都是园区出来的。找小编要我联系方式，明天中午12点前没说法，我就先去码，然后各大站点全网曝光，同时国内安…
代办证件垫付费用请尽快归还 有认识这两个人的帮忙问一声，之前让人代办的证件还要不要？哪怕直接说不需要了也行。 请把我帮你们垫付的费用还回来，证件你们拿走，账单我这边都留着。 大半年了，你俩是没钱还是怎么的？至少给个消息吧。 最后再给一个星期时间自己联系我处理。下周二前还没信的话，就把你们所有个人信息发国内反诈警察，本地警局同步入档备案。别他妈再装死了。
#骗子曝光 #陈帅宇 陈帅宇，贵州安顺的挂壁仔，手机号18593810761，专门卧底配合警察钓鱼抓偷渡的。 这狗东西贵州佬四处骗人，各个公司都接他，他还同时联系多家公司让人买票去接。自己一直作妖，一会儿说护照直接卡关，一会儿又说要验资没钱，就让人转钱、开酒店吃喝玩乐。 结果到了昆明人直接玩消失，联系不上了。死妈的货，望各公司赶紧避雷，千万别再接这人！
特区遇老挝妹结果被绿了 今年3月第一次踏进特区，泰北气候，赵伟管辖的范围，一切挺人性化，灰产界算一股清流。物价相对友好，公司规矩不能禁足，很自由。最吸引人的当然是老挝妹。 在大门口等外卖时碰到了阿芳，身高168，长得不算特别精致，身材前凸后翘全是原装，关键是性格好相处（前提是你得长得跟我一样帅）。直接加了WS，当时我住单间，约出来吃烧烤喝了点酒就确认了男女朋友关系，那段时间挺甜蜜。 后来因为必须回国处理家事，我回去了两个星期左右。回来后小别胜新婚，有空就在一起。忽然有一天她说怀孕了，我又惊喜又意外。我这人比较佛系，也喜欢小孩，就建议她生下来。结果她直接拒绝，再三追问下才弄清楚——他妈的老子被绿了！！！ 老挝妹玩玩就好，兄弟们别当真。老挝没有雪，特区没有爱。还是好好认真敲键盘赚钱，比什么都重要。
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#马来资讯 仙本那水警截获11公斤冰毒 8月12日，沙巴第四区水警部队昨天凌晨大概1时45分，在仙本那邦邦岛甘榜特鲁山胡绒海域展开行动，成功起获超过11公斤疑似冰毒。 沙巴第四区水警部队指挥官阿末阿姆里阿都拉曼助理总监说，部队是根据毒品贩运情报出动的，途中发现一艘可疑快艇。执法人员靠近时，船上一名男子直接跳海往陆地逃，警方马上搜捕，但没找到人。 检查被遗弃的快艇后，发现11个包裹，里面全是疑似冰毒的透明晶体块，毛重约11.06公斤。
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#柬埔寨 #菲律宾 #电诈头目 曝光两名柬埔寨电诈头目，中国籍福建泉州大盘总。 苏文水（外号叶峰），福建省泉州人。陈建波（外号小福），也是福建省泉州人。两人是亲戚关系。 早期在柬埔寨和菲律宾开设多个杀猪盘和赌博网站，盘口名称有美高梅、美狮、贵宾会等等。后来到了柬埔寨，开酒吧KTV、餐厅，利用酒吧KTV老板身份做掩护。戈公镇上最大的酒吧KTV就是他们俩开的，人尽皆知。 此后两人就长期盘踞在柬埔寨戈公省白宫度假村老三楼，继续搞诈骗。高峰期盘口有数百名员工，包括中国人、缅甸人、老挝人、越南人、马来西亚人、泰国人。公司属于长期封闭式管理，除了跟他们关系好的，其他人都不能外出。 公司长期压榨、辱骂、体罚、殴打员工，恶意克扣工资，各种找理由罚款，恶意开除还不结工资。还有人口买卖、拉赔付、扣押护照逼家里人打款赔付等等恶心事。两人阴险狡诈，手段狠辣，经常骚扰、威胁多名女员工陪他们出去吃饭喝酒过夜。 2026年2月份公司搬到塞尔维亚、…
#柬埔寨 #曝光渣男 #宇白 #骗色传病 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。后面他要包养我，一个月给1万美金，叫我不要上班。 我那个时候还有男朋友，男朋友也是跟他一个公司，都在大老板冬天下面做代理。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，一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，后面直接不理我了。 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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Showing the 12 most recent of 142 posts we hold for @dongnanya_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.
Citation-graph rank — 334,978 of 1,151,006entries 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 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.
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.
“东南亚新币曝光|新闻大事件” (@dongnanya_xinbibaoguang), 89,202 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/dongnanya_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.