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Channel

全网大事件吃瓜曝光

@quanwangdsj

On this record: Topic · Observations · Channels linked by matching posts · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry

59,289subscribers

-5,739 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 31,623–100,000.

Register entry

Telegram ID-1001765201531
TypeChannel
Username@quanwangdsj
Description唯一免费投稿: @dnykn6 唯一商务合作: @ekko520 ⚠️:投稿账号不谈商务!!! 我们致力于揭露全球热点事件与内幕真相,分享最新的吃瓜资讯,让您在轻松的氛围中获取最真实的曝光内容。关注我们,一起吃瓜看世界!注意:本频道发布的相关资讯均来自于网友投稿,真假请自行甄别,本频道概不做审核。
CreatedBetween 1 December 2021 and 30 April 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live11 November 2026
Measurements held64
Confirmed unchanged1 time, most recently 11 November 2026
On Telegramt.me/quanwangdsj

Topic

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 43% 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 in near-verbatim form on 12 other registered channels. This entry also sits inside a group of 3 channels linked by matching posts, directly or through other channels in the group; two members of the group may share no posts with each other. 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)
Posted firstThenOverlapGap
@quanwangdsj/125375 · this entry8 Aug 2026, 15:10 UTC@huisedny/1220428 Aug 2026, 15:10 UTC1.00under a minute
@quanwangdsj/128589 · this entry21 Aug 2026, 16:12 UTC@huisedny/12524321 Aug 2026, 16:12 UTC1.00under a minute
@quanwangdsj/130755 · this entry30 Aug 2026, 13:43 UTC@huisedny/12739130 Aug 2026, 13:43 UTC1.00under a minute
@quanwangdsj/132451 · this entry6 Sept 2026, 16:33 UTC@huisedny/1290736 Sept 2026, 16:33 UTC1.00under a minute
@quanwangdsj/143716 · this entry1 Nov 2026, 08:42 UTC@huisedny/1403021 Nov 2026, 08:42 UTC1.00under a minute
@quanwangdsj/144379 · this entry5 Nov 2026, 06:17 UTC@huisedny/1409725 Nov 2026, 06:17 UTC1.00under a minute
Channels this entry shares post bodies with, where at least one matching post pair has no forward credit between the two channels, or to a common source, recorded in our data
ChannelMatching postsText overlapTypical gapPublished first
@huisedny636 (7/8 hand-verifiable sample passed)1.00under a minutethis entry (537–99)
@gtkx1209 (8/8 hand-verifiable sample passed)1.00under a minute@gtkx1 (164–45)
@DNYBG234168 (7/8 hand-verifiable sample passed)1.00under a minute@DNYBG234 (164–4)
@xhuids668122 (6/8 hand-verifiable sample passed)1.00under a minutethis entry (122–0)
@jianpuzhai_xinbibaoguang121 (6/8 hand-verifiable sample passed)1.0027 minutes@jianpuzhai_xinbibaoguang (121–0)
@bxc888104 (8/8 hand-verifiable sample passed)1.005.4 hoursthis entry (104–0)
@JPZXGFBI103 (5/8 hand-verifiable sample passed)1.0024 minutes@JPZXGFBI (103–0)
@DNYXW00895 (7/8 hand-verifiable sample passed)1.007.0 hoursthis entry (95–0)
@jianpuzhai_xinwen74 (6/8 hand-verifiable sample passed)1.0028 minutes@jianpuzhai_xinwen (74–0)
@jianpuzhai_baoguang73 (6/8 hand-verifiable sample passed)1.0030 minutes@jianpuzhai_baoguang (73–0)
@JPZJBFBI36 (8/8 hand-verifiable sample passed)1.0028 minutes@JPZJBFBI (19–17)
@baoguang_9926 (7/8 hand-verifiable sample passed)1.0031 minutesthis entry (21–5)

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. 904 of the 904 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 1,892 comparable posts for this entry, running 7 August 2026 to 13 November 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).

Of the group of 3 channels, the one whose matching posts we hold earliest is @gtkx1. That is a statement about our reading window, not a claim of authorship.

Recorded under the keys clone_copy · clone_mutual · clone_source, last confirmed 14 November 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.

Channels linked by matching posts

This channel is in a group of 3 registered channels linked by matching posts, directly or through other channels in the group. This channel may share no posts with some of the channels listed below, and listed channels may share none with each other. Links are found by comparing text fingerprints across every channel on the register.

Which channel, if either, published first is deliberately not shown in this list. “First” could only mean first in our own crawl, which depends on how deep we happened to reach into each channel’s history, not on when the content was actually first posted. Our one hand-check read 45 of the highest-confidence flagged pairs against the live Telegram pages. In 18 of them the live page showed a “Forwarded from” credit that our database had no record of, so reading that pair as an unattributed copy was wrong; the check did not measure who published first. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Near-verbatim 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.

Growth

59,28968,25163,7707 August 202611 November 2026
64 measurements spanning 96 days, net -5,739. 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 57,945–69,595 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 64
Measured (UTC)SubscribersChange
11 Nov 2026, 22:4559,289-194
9 Nov 2026, 23:0959,483-343
8 Nov 2026, 12:0559,826-202
7 Nov 2026, 09:3460,028-265
6 Nov 2026, 09:4560,293-173
5 Nov 2026, 10:2560,466-103
4 Nov 2026, 10:3760,569-223
3 Nov 2026, 11:0660,792-318
2 Nov 2026, 12:4661,110-61
1 Nov 2026, 13:5861,171-226
31 Oct 2026, 11:3661,397-207
30 Oct 2026, 12:3661,604-282
29 Oct 2026, 09:1761,886-225
28 Oct 2026, 05:5062,111-143
27 Oct 2026, 04:0762,254-125
26 Oct 2026, 02:3862,379-87
25 Oct 2026, 00:5662,466-231
23 Oct 2026, 22:0062,697-178
23 Oct 2026, 00:2962,875-215
22 Oct 2026, 00:2063,090first reading

Engagement

2,828 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 200 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
1.35%
avg views ÷ 59,289 subscribers
Avg views / post
798
636 posts measured
Reaction rate
0.242%
reactions ÷ views · ER floor
Posts in window
806
of 2,828 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 11 of 636 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 14 November 2026
Posts held2,828 (7 August 2026 – 14 November 2026)
Views total507,749
Reactions total9
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken14 Nov 2026, 21:55 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

Photos
≈94,100
Videos
≈13,500
Links
≈673

Lifetime counters from Telegram’s own channel header, read 14 November 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.

Video runtime
1h 34m
Average length
22s

Measured directly from 255 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

9 reactions across 9 posts, in 1 kind.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
👍9100.0%

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 11 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 9 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 9 October 2026 to 14 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 806 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).

14 Nov 2026, 18:30 UTC≈1,060 viewsread 14 November 2026
Photo

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14 Nov 2026, 18:00 UTC≈1,180 viewsread 14 November 2026
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14 Nov 2026, 17:00 UTC970 viewsread 14 November 2026
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14 Nov 2026, 16:10 UTC930 viewsread 14 November 2026
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14 Nov 2026, 16:03 UTC≈1,220 viewsread 14 November 2026
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14 Nov 2026, 14:55 UTC≈1,240 viewsread 14 November 2026
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14 Nov 2026, 14:49 UTC725 viewsread 14 November 2026
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#网友分享 这次高尔夫之旅本应是我退休后的第一个正式假期。几位老友说服了我,邀我一同前往泰国度过两周。 我了解芭堤雅的​​情况,对那里的夜生活也并不反感,但我当时并无意寻找伴侣。我刚卖掉了自己的生意,又有养老金作为保障,多年来第一次感到无拘无束,不必向任何人交代行踪,这种自由让我倍感惬意。 一天晚上,我们正在喝酒时,一位名叫西琳(Sirin)的泰国女子加入了我们的桌子。那天晚上我们大部分时间都待在一起,临走前还交换了联系方式。 第二天一早,她给我发了消息,于是我们又见了一面。我们一起吃了午饭,参观了芭堤雅郊外的一座寺庙,还共度了整个晚上。此后,我几乎没再怎么见过我的朋友们,因为直到我启程回国,我和西琳几乎每天都待在一起。 回到家后,我已经在考虑退休后每年在泰国住上几个月了;没过几周,我就又订好了下一次的行程。 就在我出发前不久,西琳打来电话,语气十分焦急,说她叔叔在素林(Surin)附近遭遇意外,受了重伤。她发来了在…

Showing the 12 most recent of 2,828 posts we hold for @quanwangdsj. 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

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.

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 11 November 2026 — this entry's latest reading, not the date you are reading this.

“全网大事件吃瓜曝光” (@quanwangdsj), 59,289 subscribers as measured 11 November 2026. Telegram Register, tgregister.com/channel/quanwangdsj.

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.