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Channel

菲律宾新闻|斑马曝光|philippine news

@Feilvbin_xinwen

On this record: Topic · Observations · Also posting the same content · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry

88,939subscribers

-7,202 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-1001870904514
TypeChannel
Username@Feilvbin_xinwen
Description斑马曝光业务受理范围: 1.投稿爆料 2.澄清删帖 3.广告付费 🌏东南亚灰产新闻曝光: @Banma_xinwen 🇦🇪迪拜灰产新闻曝光: @Dubai_xinwen 🇵🇭菲律宾灰产新闻曝光: @Feilvbin_xinwen 🇰🇭柬埔寨灰产新闻曝光: @jianpuzhai_xinwen 🇹🇭🇲🇲🇱🇦金三角灰产新闻曝光: @jinsanjiao_xinwen ☎️ 爆料投稿: @banma_baoguang @banma_baoguang_bot(双向客服机器人)
CreatedBetween 1 October 2022 and 30 September 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live18 September 2026
Measurements held32
Confirmed unchanged1 time, most recently 18 September 2026
On Telegramt.me/Feilvbin_xinwen

Topic

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 58% 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 1 other registered channel. 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
@Feilvbin_xinwen/51433 · this entry7 Aug 2026, 06:20 UTC@feilvbin_xinbibaoguang/169677 Aug 2026, 06:20 UTC1.00under a minute
@Feilvbin_xinwen/51439 · this entry7 Aug 2026, 09:08 UTC@feilvbin_xinbibaoguang/169717 Aug 2026, 09:08 UTC1.00under a minute
@Feilvbin_xinwen/51441 · this entry7 Aug 2026, 10:59 UTC@feilvbin_xinbibaoguang/169757 Aug 2026, 10:59 UTC1.00under a minute
@Feilvbin_xinwen/51446 · this entry7 Aug 2026, 11:07 UTC@feilvbin_xinbibaoguang/169787 Aug 2026, 11:07 UTC1.00under a minute
@Feilvbin_xinwen/51449 · this entry7 Aug 2026, 14:46 UTC@feilvbin_xinbibaoguang/169797 Aug 2026, 14:46 UTC1.00under a minute
@Feilvbin_xinwen/51450 · this entry7 Aug 2026, 15:16 UTC@feilvbin_xinbibaoguang/169827 Aug 2026, 15:16 UTC1.00under a minute
Every channel this entry shares post bodies with
ChannelMatching postsText overlapTypical gapPublished first
@feilvbin_xinbibaoguang7 (6/7 hand-verifiable sample passed)1.00under a minute@feilvbin_xinbibaoguang (70)

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. 7 of the 7 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 13 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 2, the earliest publisher we hold is @Feilvbin_xinwen — which is this entry. That is a statement about our reading window, not a claim of authorship.

Recorded under the key clone_copy, 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 1 other registered channel, 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.

Growth

88,93996,14192,5407 August 2026 — 96,141 subscribers8 August 2026 — 96,070 subscribers9 August 2026 — 95,864 subscribers10 August 2026 — 94,852 subscribers11 August 2026 — 94,617 subscribers12 August 2026 — 94,495 subscribers13 August 2026 — 94,329 subscribers14 August 2026 — 94,129 subscribers16 August 2026 — 93,875 subscribers17 August 2026 — 93,668 subscribers18 August 2026 — 93,520 subscribers19 August 2026 — 93,363 subscribers20 August 2026 — 93,256 subscribers21 August 2026 — 93,118 subscribers23 August 2026 — 92,885 subscribers24 August 2026 — 92,548 subscribers26 August 2026 — 92,398 subscribers26 August 2026 — 92,293 subscribers27 August 2026 — 92,217 subscribers29 August 2026 — 92,132 subscribers30 August 2026 — 92,007 subscribers31 August 2026 — 91,882 subscribers1 September 2026 — 91,787 subscribers2 September 2026 — 91,635 subscribers3 September 2026 — 91,374 subscribers5 September 2026 — 91,164 subscribers8 September 2026 — 90,627 subscribers11 September 2026 — 89,696 subscribers12 September 2026 — 89,396 subscribers14 September 2026 — 89,197 subscribers16 September 2026 — 89,097 subscribers18 September 2026 — 88,939 subscribers7 August 202618 September 2026
32 measurements spanning 42 days, net -7,202. 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 87,859–97,221 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 32
Measured (UTC)SubscribersChange
18 Sept 2026, 12:2188,939-158
16 Sept 2026, 04:4089,097-100
14 Sept 2026, 09:1989,197-199
12 Sept 2026, 19:5789,396-300
11 Sept 2026, 00:2189,696-931
8 Sept 2026, 03:5890,627-537
5 Sept 2026, 01:3891,164-210
3 Sept 2026, 09:4691,374-261
2 Sept 2026, 00:3491,635-152
1 Sept 2026, 04:0591,787-95
31 Aug 2026, 04:0791,882-125
30 Aug 2026, 04:2892,007-125
29 Aug 2026, 01:4592,132-85
27 Aug 2026, 22:2492,217-76
26 Aug 2026, 21:4392,293-105
26 Aug 2026, 00:2492,398-150
24 Aug 2026, 22:4792,548-337
23 Aug 2026, 06:1692,885-233
21 Aug 2026, 14:4793,118-138
20 Aug 2026, 12:5793,256first reading

Engagement

1,114 posts held, back to 7 August 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 96 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
3.89%
avg views ÷ 88,939 subscribers
Avg views / post
3,460
558 posts measured
Reaction rate
0.085%
reactions ÷ views · ER floor
Posts in window
736
of 1,114 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 74 of 558 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 22 September 2026
Posts held1,114 (7 August 202622 September 2026)
Views total1,929,862
Reactions total212
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken22 Sept 2026, 23:15 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
43,000
Videos
4,710
Links
4,860

Lifetime counters from Telegram’s own channel header, read 22 September 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 32m
Average length
35s

Measured directly from 158 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

2,041 reactions across 205 posts, in 14 distinct kinds. The most used accounts for 12.2% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
👍24912.2%
🎉24111.8%
😍23111.3%
🥰23111.3%
22811.2%
❤‍🔥21810.7%
💯21310.4%
🔥2029.90%
🤩2029.90%
80.392%
😁80.392%
👏70.343%
👀20.098%
🤣10.049%

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 205 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 2,041 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 12 August 2026 to 22 September 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

22 Sept 2026, 23:00 UTC≈3,600 viewsread 22 September 2026
Photo

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22 Sept 2026, 20:06 UTC≈2,150 viewsread 22 September 2026
Video

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22 Sept 2026, 18:11 UTC≈5,900 viewsread 22 September 2026
Video

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22 Sept 2026, 18:01 UTC≈3,460 viewsread 22 September 2026
Photo

#菲律宾资讯:菲政府称暂不上调公共交通票价 2026年9月23日,菲律宾马尼拉——因中东局势推高油价,马科斯政府表示暂无意上调公共交通票价。 总统府新闻官卡斯特罗称,交通部希望票价上涨成为最后手段,政府正通过燃油折扣、免费通行及定向补贴等措施,缓解司机压力。 交通部长洛佩斯表示,任何票价上调都须考虑通胀影响,目前相关研究仍在进行。

22 Sept 2026, 17:00 UTC≈3,550 viewsread 22 September 2026
Video

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22 Sept 2026, 16:00 UTC≈3,490 views1 reactionsread 22 September 2026
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👍1

22 Sept 2026, 14:00 UTC≈3,840 viewsread 22 September 2026
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22 Sept 2026, 13:31 UTC≈2,700 viewsread 22 September 2026
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#菲律宾资讯:两天抓捕23人缴获逾150万比索毒品 9月21日至22日,菲律宾Soccsksargen地区警方开展同步打击犯罪行动(SACLEO),共抓捕9名涉毒人员,缴获价值超过150万菲律宾比索的毒品。 警方称,在苏丹库达拉省伊苏兰市的一次深夜行动中,两名涉嫌贩毒人员被当场抓获,查获约106.57克疑似冰毒(Shabu),毒品价值约72.47万比索。 此外,警方在该地区开展的另外6次突袭行动中,再抓获7名涉毒人员,缴获价值约78.95万比索的冰毒。 此次行动还抓获14名在逃人员,4人主动上交无证枪支,并查获价值约22万比索的走私香烟。

Showing the 12 most recent of 1,114 posts we hold for @Feilvbin_xinwen. 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 4 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.

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 18 September 2026 — this entry's latest reading, not the date you are reading this.

“菲律宾新闻|斑马曝光|philippine news” (@Feilvbin_xinwen), 88,939 subscribers as measured 18 September 2026. Telegram Register, tgregister.com/channel/Feilvbin_xinwen.

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.