National news — 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 9 August 2026 and assigned it the closest of 31 fixed categories, at 73% 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.
Observations
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.
Content that also appears on other registered channels
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.
Matching posts — open both and compare (6 of the pairs behind the counts below)
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. 6 of the 6 matches recorded here fall after that date and carried no header when we read them. The rest predate reliable capture and are not evidence either way.
“Published first” means first in this corpus. We hold 20 comparable posts for this entry, running 7 August 2026 to 7 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.
Verbatim republication has three causes and the text separates only two: a clone/mirror, unattributed copy-paste, or BOTH channels copying a common third source that neither attributes. The spread filter (content held by at most 8 channels) reduces the third and does not remove it.
'Earliest' means earliest IN THIS CORPUS. A channel ingested one page deep will look younger than a neighbour ingested in full; corpus_coverage above is there to be checked before the direction is believed.
shared_verified_est extrapolates the sampled pass rate over the full narrow match count; sampled/passed are the numbers actually measured.
Absence of a forward header is not proof of intent: Telegram lets a channel disable forward attribution, and a credit written in the body is not parsed as attribution here (mention_edge_either_way above is the closest available signal).
Across the whole group of 3, the earliest publisher we hold is @DNYQZZP. That is a statement about our reading window, not a claim of authorship.
Recorded under the keys clone_copy · clone_source, last confirmed 7 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.
Also posting the same content
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.
9 measurements spanning 8 days, net -13,411. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 103,449–120,884 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
15 Aug 2026, 20:08
105,461
-1,422
14 Aug 2026, 06:58
106,883
-3,820
12 Aug 2026, 20:34
110,703
-1,639
11 Aug 2026, 22:41
112,342
-2,822
10 Aug 2026, 23:03
115,164
-1,012
9 Aug 2026, 22:12
116,176
-1,198
8 Aug 2026, 21:10
117,374
-1,108
8 Aug 2026, 00:12
118,482
-390
7 Aug 2026, 14:45
118,872
first reading
Engagement
242 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 22 pagesof Telegram’s post history, 20 posts per page.
ERR · 30 days
2.84%
avg views ÷ 105,461 subscribers
Avg views / post
3,000
242 posts measured
Reaction rate
0.046%
reactions ÷ views · ER floor
Posts in window
242
of 242 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. It is computed over the 10 of 242 measured posts that carry a reaction reading, and over those same posts' views.
What these figures were computed from
Window
Rolling 30 days · latest post in window 15 August 2026
Posts held
242 (7 August 2026 – 15 August 2026)
Views total
725,021
Reactions total
15
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
15 Aug 2026, 19:39 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
Video runtime
32m 28s
Average length
22s
Measured directly from 89 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.
Reaction mix
15 reactions across 10 posts, in 7 distinct kinds. The most used accounts for 20.0% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
🎉
3
20.0%
💯
3
20.0%
🔥
3
20.0%
😇
3
20.0%
❤
1
6.67%
👌
1
6.67%
🤩
1
6.67%
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 10 of the 242 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 15reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 242 most recent posts we hold, published 7 August 2026 to 15 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.
Showing the 12 most recent of 242 posts we hold for @xinwen118. 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
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.
Channels Telegram recommends alongside this one
Telegram’s own answer, not this register’s.When this register asks Telegram’s API what is similar to this channel, this is the list it returns, in the exact order Telegram returns it — never re-sorted by subscribers or by anything else this register measures. The relationship, and the order, are Telegram’s; we record them and date them, and make no claim of our own about which of these channels actually resemble this one.
Read from Telegram’s recommendation API, most recently 15 August 2026. Telegram holds a list like this for a small and growing share of the register — how this is measured, and why most channel pages show nothing here.
Appears in Telegram’s recommendations for other channels
The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.
东南亚狗推快讯（曝光）📱‼️ @gtkx1 · 168,496 Telegram ranks this channel #6 of 76 here — alongside 75 others — read 14 August 2026
东南亚曝光大事件新闻头条 exposure @AoneExp · 120,060 Telegram ranks this channel #8 of 74 here — alongside 73 others — read 14 August 2026
东南亚曝光频道 @BG2288 · 107,332 Telegram ranks this channel #9 of 72 here — alongside 71 others — read 15 August 2026
全球华人大事件曝光 @qqhrdsjbg · 237,814 Telegram ranks this channel #13 of 71 here — alongside 70 others — read 11 August 2026
缅甸缅北东南亚新闻曝光 @nx123 · 799,205 Telegram ranks this channel #14 of 64 here — alongside 63 others — read 13 August 2026
柬埔寨新闻《柬埔寨曝光》 @sii76 · 199,655 Telegram ranks this channel #14 of 61 here — alongside 60 others — read 11 August 2026
东南亚大爆料（曝光） @bbsooo · 107,619 Telegram ranks this channel #15 of 64 here — alongside 63 others — read 14 August 2026
东南亚大事件｜曝光｜悬赏｜投稿🏆 @dyy83 · 115,519 Telegram ranks this channel #16 of 69 here — alongside 68 others — read 14 August 2026
东南亚🇨🇿今日头条 @huohu158 · 95,767 Telegram ranks this channel #17 of 74 here — alongside 73 others — read 15 August 2026
泰国新闻|华人资讯曝光|thailand news @taiguohuarenzixun · 106,360 Telegram ranks this channel #17 of 71 here — alongside 70 others — read 15 August 2026
迪拜新闻|海豹资讯曝光|dubai news @dibai_01 · 93,465 Telegram ranks this channel #19 of 50 here — alongside 49 others — read 15 August 2026
东南亚大事件实时新闻 @sssvip2 · 279,176 Telegram ranks this channel #19 of 68 here — alongside 67 others — read 11 August 2026
曝光骗子 @baoguang2022 · 138,147 Telegram ranks this channel #21 of 76 here — alongside 75 others — read 15 August 2026
今日聚焦曝光 @a0159 · 129,087 Telegram ranks this channel #21 of 67 here — alongside 66 others — read 13 August 2026
全球大事件|新闻|曝光 @QQDS999 · 240,538 Telegram ranks this channel #21 of 76 here — alongside 75 others — read 11 August 2026
东南亚新闻/黑料曝光 @BG6668 · 114,255 Telegram ranks this channel #22 of 57 here — alongside 56 others — read 14 August 2026
东南亚漂泊日记-柬埔寨大事件曝光 @GGooGG66 · 122,176 Telegram ranks this channel #22 of 64 here — alongside 63 others — read 14 August 2026
迪拜/东南亚/大事件曝光生活资讯攻略 @tingyu0002 · 209,339 Telegram ranks this channel #22 of 27 here — alongside 26 others — read 11 August 2026
柬埔寨大事件🇰🇭西港日记 @xinwenhc · 104,248 Telegram ranks this channel #23 of 67 here — alongside 66 others — read 15 August 2026
东南亚曝光吧⚠️吃瓜爆料 @baoguangba088 · 245,358 Telegram ranks this channel #24 of 68 here — alongside 67 others — read 11 August 2026
东南亚🌍安危大事件 （💋菲 柬 迪 泰 缅 老挝💋）爆料 @quanqiubaoliao · 232,295 Telegram ranks this channel #25 of 71 here — alongside 70 others — read 11 August 2026
🇵🇭菲行者：吃瓜中心 @feixingzhe_cgzx · 174,629 Telegram ranks this channel #28 of 63 here — alongside 62 others — read 12 August 2026
缅甸新闻|华人资讯曝光|myanmar news @miandianhuarenzixun · 97,061 Telegram ranks this channel #29 of 77 here — alongside 76 others — read 16 August 2026
TG第一曝光频道 @tg88f · 125,743 Telegram ranks this channel #29 of 75 here — alongside 74 others — read 15 August 2026
This channel appears in 51 seed channels' Telegram-generated recommendation lists in total, of which the 24 where it ranks highest are shown above. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
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 15 August 2026 — this
entry's latest reading, not the date you are reading this.
“迪拜新闻|华人资讯大曝光” (@xinwen118), 105,461 subscribers as measured 15 August 2026. Telegram Register, tgregister.com/channel/xinwen118.
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.
