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 49% 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 7 other registered channels. This entry also sits inside a group of 8 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)
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
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 48 comparable posts for this entry, running 6 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).
Of the group of 8 channels, the one whose matching posts we hold earliest is @duterte. 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.
Channels linked by matching posts
This channel is in a group of 8 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.
620 measurements spanning 96 days, net -24,015. 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 64,656–99,677 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 620
Measured (UTC)
Subscribers
Change
11 Nov 2026, 00:20
68,697
-45
10 Nov 2026, 22:06
68,742
-67
10 Nov 2026, 13:15
68,809
-30
10 Nov 2026, 10:37
68,839
-4
10 Nov 2026, 10:19
68,843
-15
10 Nov 2026, 09:38
68,858
-18
10 Nov 2026, 08:51
68,876
-75
10 Nov 2026, 05:50
68,951
-71
10 Nov 2026, 02:49
69,022
-43
9 Nov 2026, 23:55
69,065
-316
9 Nov 2026, 10:47
69,381
-64
9 Nov 2026, 07:04
69,445
-105
8 Nov 2026, 23:55
69,550
no change
8 Nov 2026, 23:37
69,550
-20
8 Nov 2026, 22:20
69,570
-2
8 Nov 2026, 22:05
69,572
-75
8 Nov 2026, 19:50
69,647
-5
8 Nov 2026, 18:07
69,652
-122
8 Nov 2026, 13:40
69,774
-11
8 Nov 2026, 12:59
69,785
first reading
Engagement
2,631 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 202 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
9.24%
avg views ÷ 68,697 subscribers
Avg views / post
6,350
824 posts measured
Reaction rate
0.066%
reactions ÷ views · ER floor
Posts in window
825
of 2,631 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 625 of 824 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 10 November 2026
Posts held
2,631 (6 August 2026 – 10 November 2026)
Views total
5,230,572
Reactions total
2,842
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
10 Nov 2026, 18:56 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
7h 01m
Average length
34s
Measured directly from 744 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
3,483 reactions across 729 posts, in 23 distinct kinds. The most used accounts for 22.2% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
custom 5424813272765330422
773
22.2%
👍
496
14.2%
🥰
432
12.4%
👏
429
12.3%
🔥
398
11.4%
🎉
381
10.9%
🤩
359
10.3%
❤
117
3.36%
💯
20
0.574%
😍
13
0.373%
😭
12
0.345%
👌
10
0.287%
❤🔥
9
0.258%
🐳
9
0.258%
🤬
7
0.201%
😢
4
0.115%
🙏
4
0.115%
🌚
3
0.086%
🏆
2
0.057%
👻
2
0.057%
3 further kinds
3
0.086%
Custom emoji. One row above is a Telegram custom emoji, which the public preview renders as an element carrying only a numeric id — no character, and no image we can reach. The id is printed as-is rather than substituted with a look-alike glyph, because a stand-in would be our invention showing where a measurement should be. The count beside it is Telegram’s.
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 735 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 3,483 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 5 October 2026 to 10 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: 7 of 825 posts held from the last 30 days (0.848%) 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).
Showing the 12 most recent of 2,631 posts we hold for @feilongwang. 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
Named by 71 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. The 24 listed below are the most frequent namers; the rest are counted above but not each listed.
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
2
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
2
vacant every time we have ever looked
@feilongwang 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.
Never seen alive
References a handle that is not a live channel — we have no record it ever was one.
@jvip8888 named in 3 posts, 5 September 2026 – 7 September 2026
@sahuhuhu named in 1 post, 16 September 2026 – 16 September 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 18 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.
菲律宾新闻 @flbxinwen01 · 23,191 Telegram ranks this channel #1 of 20 here — alongside 19 others — read 25 September 2026
柬埔寨头条 🔰 @tnaot · 21,667 Telegram ranks this channel #1 of 19 here — alongside 18 others — read 21 September 2026
华人头条大事件曝光 @huarenvvip · 31,360 Telegram ranks this channel #2 of 19 here — alongside 18 others — read 30 August 2026
东南亚安危头条事件🅥 @AnWei08 · 61,021 Telegram ranks this channel #2 of 55 here — alongside 54 others — read 24 August 2026
头条事件 @toutiaoshijian · 66,725 Telegram ranks this channel #2 of 33 here — alongside 32 others — read 18 August 2026
菲律宾华人事件 @svip40 · 129,751 Telegram ranks this channel #2 of 37 here — alongside 36 others — read 17 August 2026
【菲律宾新闻】最新爆光 @baoguang211 · 8,202 Telegram ranks this channel #3 of 24 here — alongside 23 others — read 17 September 2026
曝光骗局-大事件频道-吃瓜搞笑-东南亚新闻 @baoguang · 33,486 Telegram ranks this channel #3 of 9 here — alongside 8 others — read 10 September 2026
热点新闻 @redian3 · 62,099 Telegram ranks this channel #3 of 40 here — alongside 39 others — read 23 August 2026
斯里兰卡头条新闻曝光 @baoguangee · 198,457 Telegram ranks this channel #3 of 46 here — alongside 45 others — read 11 August 2026
《今日新闻》 @cctvPH · 131,604 Telegram ranks this channel #3 of 22 here — alongside 21 others — read 11 August 2026
新闻哥头条吃瓜每日热点 @yewaiTQ · 24,955 Telegram ranks this channel #4 of 20 here — alongside 19 others — read 23 September 2026
东南亚 曝光 悬赏 新闻 @DNYXW008 · 73,667 Telegram ranks this channel #4 of 65 here — alongside 64 others — read 13 August 2026
全网华人曝光吧 @QWHRBGB · 142,038 Telegram ranks this channel #4 of 66 here — alongside 65 others — read 11 August 2026
全球大事件🌍 「TIKTOK官方」 @qqdsj · 166,859 Telegram ranks this channel #4 of 37 here — alongside 36 others — read 11 August 2026
柬埔寨头条事件️🅥 @HR8877 · 317,788 Telegram ranks this channel #4 of 76 here — alongside 75 others — read 10 August 2026
博度东南亚大事件 @bdtime @bodutt · 66,197 Telegram ranks this channel #5 of 62 here — alongside 61 others — read 21 August 2026
菲律宾新闻大事件 @flb608 · 68,636 Telegram ranks this channel #5 of 80 here — alongside 79 others — read 14 August 2026
今日全网曝光频道 @bg855 · 2,736 Telegram ranks this channel #5 of 40 here — alongside 39 others — read 10 August 2026
吃瓜新闻大曝光 @jiuboo · 14,043 Telegram ranks this channel #6 of 25 here — alongside 24 others — read 21 September 2026
全网吃瓜爆料|网红黑料｜新闻大事件 @chiguabaoliaozhan · 13,301 Telegram ranks this channel #6 of 13 here — alongside 12 others — read 17 September 2026
东南亚热点资讯 @rdzx0 · 87,328 Telegram ranks this channel #6 of 80 here — alongside 79 others — read 18 August 2026
菲律宾新闻|华人资讯曝光|philippine news @feilvbinhuarenzixun · 68,095 Telegram ranks this channel #6 of 82 here — alongside 81 others — read 16 August 2026
东南亚有话说 @shuoo @db933 · 186,963 Telegram ranks this channel #6 of 65 here — alongside 64 others — read 11 August 2026
This channel appears in 119 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 11 November 2026 — this
entry's latest reading, not the date you are reading this.
“菲龙网新闻中文媒体【官方】” (@feilongwang), 68,697 subscribers as measured 11 November 2026. Telegram Register, tgregister.com/channel/feilongwang.
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.
