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 the other topics.
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 3 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. 8 of the 8 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 30 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 4, the earliest publisher we hold is @bx777 — which is this entry. That is a statement about our reading window, not a claim of authorship.
Recorded under the keys clone_mutual · 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.
Also posting the same content
This channel’s posts match, word for word or near enough, posts on 3 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.
228 measurements spanning 89 days, net -4,651. 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 27,837–48,464 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 228
Measured (UTC)
Subscribers
Change
4 Nov 2026, 13:20
30,217
-6
4 Nov 2026, 10:37
30,223
-5
4 Nov 2026, 06:11
30,228
+9
4 Nov 2026, 02:16
30,219
-78
3 Nov 2026, 14:56
30,297
-57
3 Nov 2026, 09:28
30,354
-80
3 Nov 2026, 02:55
30,434
no change
3 Nov 2026, 02:50
30,434
-204
2 Nov 2026, 12:29
30,638
no change
2 Nov 2026, 11:05
30,638
+3
2 Nov 2026, 05:57
30,635
no change
2 Nov 2026, 02:19
30,635
-98
1 Nov 2026, 11:56
30,733
no change
1 Nov 2026, 10:15
30,733
no change
1 Nov 2026, 08:05
30,733
-31
1 Nov 2026, 00:36
30,764
-59
31 Oct 2026, 13:28
30,823
-30
31 Oct 2026, 09:46
30,853
-23
31 Oct 2026, 07:16
30,876
-108
30 Oct 2026, 21:18
30,984
first reading
Engagement
2,486 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 174 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
6.04%
avg views ÷ 30,217 subscribers
Avg views / post
1,830
737 posts measured
Reaction rate
0.034%
reactions ÷ views · ER floor
Posts in window
737
of 2,486 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 116 of 737 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 4 November 2026
Posts held
2,486 (7 August 2026 – 4 November 2026)
Views total
1,345,390
Reactions total
136
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
4 Nov 2026, 10:52 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
3h 15m
Average length
30s
Measured directly from 394 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
299 reactions across 202 posts, in 9 distinct kinds. The most used accounts for 22.4% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
👍
67
22.4%
🔥
35
11.7%
🎉
33
11.0%
👏
33
11.0%
🤩
33
11.0%
⚡
30
10.0%
🥰
29
9.70%
😁
27
9.03%
❤
12
4.01%
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 210 of the 1,000 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 299 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 1,000 most recent posts we hold (the sample is capped at 1,000), published 28 September 2026 to 4 November 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.
Recent posts
Telegram’s own ‘edited’ marker: 0 of 737 posts held from the last 30 days (0%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).
#马来西亚资讯:吉打警方捣毁7个网络诈骗呼叫中心,87人落网,荒废酒店及度假村沦为诈骗据点
11月4日报道,马来西亚吉打州警方公布,今年1月至10月期间,通过多项执法行动,成功捣毁7个网络诈骗呼叫中心及诈骗集团,共逮捕87名嫌疑人。
吉打州总警长拿督阿兹里(Datuk Adzli Abu Shah)指出,落网人员包括27名马来西亚籍、33名巴基斯坦籍、15名中国籍、8名印度籍及4名孟加拉籍人士,其中75人为男性,12人为女性。
警方调查发现,诈骗集团近期逐渐改变运营方式,开始租用店屋、荒废酒店以及经营不善的度假村作为诈骗据点,利用通讯设备及科技工具实施跨境诈骗。部分荒废酒店和度假村不仅被用作呼叫中心,还被安排作为集团成员的住宿场所,以减少外界察觉。
涉案诈骗手法包括滥用银行金融交易、虚假网上万字投注、爱情诈骗、虚假工作招聘,以及冒充执法人员实施电话诈骗。
警方在行动中起获大批涉案物品,包括手机、电脑、数据机、路由器、提…
❤1
Showing the 12 most recent of 2,486 posts we hold for @bx777. 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.
Posts recorded as deleted after publishing
We recorded 1 post on @bx777 as deleted — posts this register held that were missing from the channel’s public page on two separate reads, taken from different network addresses at least an hour apart.
A deletion is not wrongdoing. This register can see that a post it held is no longer on the channel’s public page, and when — not why. Expired ad placements, reposts, rotating links and corrections all look the same. This is a count of recorded detections, not an exact total: it misses deletions we could not see, because only a post we held and later re-read inside the page can be seen to go, and it may include a small number of wrong records. How this is measured.
First seen missing
17 October 2026
Most recent seen missing
17 October 2026
Median time before seen missing
14 hours
Seen missing in the last 30 days
1
Mentions
Named by 2 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.
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.
Handles this channel named that no longer answer
Dead references
1
handles named in this channel’s posts, vacant today
Evidenced gone
0
we ourselves saw one of these resolve, at some point
Never seen alive
1
vacant every time we have ever looked
@bx777 named 1 handle 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.
Never seen alive
References a handle that is not a live channel — we have no record it ever was one.
@xj9418dl named in 4 posts, 8 August 2026 – 18 August 2026
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 27 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.
缅北悬赏通缉令(吃瓜)❖盈丰娱乐冠名🅥 @DNYTJL3 · 86,800 Telegram ranks this channel #2 of 46 here — alongside 45 others — read 14 August 2026
东南亚金三角-悬赏曝光 @jsj53 · 52,895 Telegram ranks this channel #5 of 23 here — alongside 22 others — read 20 August 2026
🇦🇪迪拜大事件/东南亚新闻 @YYL333 · 110,363 Telegram ranks this channel #7 of 66 here — alongside 65 others — read 17 August 2026
东南亚大事件️ @dsj818 · 123,453 Telegram ranks this channel #7 of 23 here — alongside 22 others — read 14 August 2026
西港日记|柬埔寨大事件 @xgrj0 · 138,070 Telegram ranks this channel #7 of 21 here — alongside 20 others — read 12 August 2026
东南亚新闻|海豹资讯曝光|news @JXBGW · 170,559 Telegram ranks this channel #8 of 21 here — alongside 20 others — read 13 August 2026
柬埔寨大事件 @blj77 @blj77 · 167,375 Telegram ranks this channel #8 of 27 here — alongside 26 others — read 12 August 2026
东南亚黑暗事件 @DNY_hasj · 196,430 Telegram ranks this channel #8 of 29 here — alongside 28 others — read 11 August 2026
海外曝光吧(全球新闻大事件)@VHHHH @vhhhh · 188,875 Telegram ranks this channel #8 of 20 here — alongside 19 others — read 11 August 2026
东南亚曝光(吃瓜)群|@XPPPP @xpppp · 305,127 Telegram ranks this channel #8 of 26 here — alongside 25 others — read 10 August 2026
西港日记|柬埔寨大事件 @jianpuzhaidashijian · 44,204 Telegram ranks this channel #9 of 44 here — alongside 43 others — read 27 August 2026
东南亚曝光揭秘社@JYGJBG @JYGJBG · 41,816 Telegram ranks this channel #9 of 53 here — alongside 52 others — read 23 August 2026
柬埔寨大事件『柬生活』🇰🇭 @jpzdny · 150,516 Telegram ranks this channel #9 of 34 here — alongside 33 others — read 12 August 2026
柬生活:便民生活导航🇰🇭 @jpzdh0 · 51,241 Telegram ranks this channel #10 of 22 here — alongside 21 others — read 25 August 2026
东南亚挨打日记 @pyzcn · 214,077 Telegram ranks this channel #11 of 47 here — alongside 46 others — read 11 August 2026
西港日记-柬埔寨通@NMSL @baoguang7 · 39,372 Telegram ranks this channel #12 of 35 here — alongside 34 others — read 24 August 2026
东南亚大事件|头条新闻 @abc03 · 206,630 Telegram ranks this channel #12 of 34 here — alongside 33 others — read 17 August 2026
西港日记/柬埔寨新闻资讯 @xigang8I8 · 147,800 Telegram ranks this channel #13 of 38 here — alongside 37 others — read 24 August 2026
东南亚大新闻 @HYY3333 · 106,556 Telegram ranks this channel #13 of 41 here — alongside 40 others — read 16 August 2026
东南亚大事件 @svip @bx666 · 462,461 Telegram ranks this channel #13 of 40 here — alongside 39 others — read 10 August 2026
东南亚大事件 @kanxia · 438,856 Telegram ranks this channel #14 of 62 here — alongside 61 others — read 10 August 2026
今日曝光 @TGBG01 · 53,800 Telegram ranks this channel #15 of 54 here — alongside 53 others — read 26 August 2026
东南亚曝光吧(吃瓜) @SB919 · 124,278 Telegram ranks this channel #15 of 68 here — alongside 67 others — read 14 August 2026
东南亚闯荡记🪐 @ac666 · 307,748 Telegram ranks this channel #15 of 61 here — alongside 60 others — read 10 August 2026
This channel appears in 78 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 4 November 2026 — this
entry's latest reading, not the date you are reading this.
“海华大事件❖6U.com娱乐首选🅥” (@bx777), 30,217 subscribers as measured 4 November 2026. Telegram Register, tgregister.com/channel/bx777.
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.