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Channel

菲律宾大事件🇵🇭海博新闻资讯

@HaiBo44

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

134,201subscribers

+52,313 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 100,000–316,228.

Register entry

Telegram ID-1001882460648
TypeChannel
Username@HaiBo44
Description🔆菲律宾大事件华人频道专注菲律宾华人最新资讯 ➖➖➖➖➖➖➖➖➖➖ 🇰🇭柬埔寨新闻大事件: @kaleminews 🇵🇭菲律宾新闻大事件: @HaiBo44 🇦🇪迪拜新闻大事件: @HaiBo11 🇲🇲缅甸新闻大事件: @FeiDu11 🇹🇭泰国新闻大事件: @HaiBo22 🤝求职&招聘 投稿爆料(免费发布): @kexin2456 📲商务合作: @kexin2456 🔆为您提供菲律宾最新的新闻大事件 为华人分享菲律宾文化,一起看菲律宾大小事 #菲律宾 #新闻 #大事件 #生活资讯 #东南亚
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 live9 September 2026
Measurements held28
Confirmed unchanged1 time, most recently 9 September 2026
On Telegramt.me/HaiBo44

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 97% 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)
Posted firstThenOverlapGap
@HaiBo44/22701 · this entry7 Aug 2026, 11:05 UTC@HaiBo11/783677 Aug 2026, 11:06 UTC1.00under a minute
@HaiBo11/783837 Aug 2026, 13:02 UTC@HaiBo44/22706 · this entry7 Aug 2026, 13:03 UTC1.00under a minute
@HaiBo11/783877 Aug 2026, 15:07 UTC@HaiBo44/22711 · this entry7 Aug 2026, 15:07 UTC1.00under a minute
@HaiBo44/22713 · this entry7 Aug 2026, 18:04 UTC@HaiBo11/783898 Aug 2026, 00:05 UTC1.006.0 hours
@HaiBo44/22715 · this entry8 Aug 2026, 00:05 UTC@HaiBo11/783918 Aug 2026, 00:05 UTC1.00under a minute
@HaiBo22/245557 Aug 2026, 11:05 UTC@HaiBo44/22701 · this entry7 Aug 2026, 11:05 UTC1.00under a minute
Every channel this entry shares post bodies with
ChannelMatching postsText overlapTypical gapPublished first
@HaiBo115 (5/5 hand-verifiable sample passed)1.00under a minutethis entry (32)
@HaiBo225 (5/5 hand-verifiable sample passed)1.00under a minute@HaiBo22 (41)

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 17 comparable posts for this entry, running 7 August 2026 to 8 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 @HaiBo22. That is a statement about our reading window, not a claim of authorship.

Recorded under the keys clone_copy · clone_mutual, 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 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.

Growth

31,791136,04883,919.57 August 2026 — 81,888 subscribers8 August 2026 — 81,797 subscribers9 August 2026 — 81,627 subscribers10 August 2026 — 81,358 subscribers11 August 2026 — 81,146 subscribers12 August 2026 — 80,942 subscribers13 August 2026 — 80,783 subscribers14 August 2026 — 80,638 subscribers16 August 2026 — 72,086 subscribers17 August 2026 — 63,816 subscribers18 August 2026 — 55,596 subscribers19 August 2026 — 55,445 subscribers20 August 2026 — 32,139 subscribers21 August 2026 — 31,973 subscribers23 August 2026 — 31,791 subscribers24 August 2026 — 34,856 subscribers25 August 2026 — 36,240 subscribers26 August 2026 — 36,180 subscribers27 August 2026 — 36,155 subscribers28 August 2026 — 92,732 subscribers29 August 2026 — 136,048 subscribers30 August 2026 — 135,978 subscribers31 August 2026 — 135,889 subscribers1 September 2026 — 135,767 subscribers2 September 2026 — 135,671 subscribers4 September 2026 — 135,477 subscribers6 September 2026 — 135,016 subscribers9 September 2026 — 134,201 subscribers134,2017 August 20269 September 2026
28 measurements spanning 33 days, net +52,313. 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 16,152–151,687 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 28
Measured (UTC)SubscribersChange
9 Sept 2026, 19:15134,201-815
6 Sept 2026, 08:17135,016-461
4 Sept 2026, 01:16135,477-194
2 Sept 2026, 12:23135,671-96
1 Sept 2026, 13:37135,767-122
31 Aug 2026, 16:14135,889-89
30 Aug 2026, 14:58135,978-70
29 Aug 2026, 14:42136,048+43,316
28 Aug 2026, 18:0492,732+56,577
27 Aug 2026, 18:2436,155-25
26 Aug 2026, 17:5836,180-60
25 Aug 2026, 20:3736,240+1,384
24 Aug 2026, 20:5434,856+3,065
23 Aug 2026, 06:4831,791-182
21 Aug 2026, 20:3531,973-166
20 Aug 2026, 18:0632,139-23,306
19 Aug 2026, 19:2755,445-151
18 Aug 2026, 21:4555,596-8,220
17 Aug 2026, 19:1963,816-8,270
16 Aug 2026, 16:2672,086first reading

Engagement

677 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 73 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
2.88%
avg views ÷ 134,201 subscribers
Avg views / post
3,870
595 posts measured
Reaction rate
0.654%
reactions ÷ views · ER floor
Posts in window
595
of 677 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 578 of 595 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 10 September 2026
Posts held677 (7 August 202610 September 2026)
Views total2,300,884
Reactions total14,640
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken10 Sept 2026, 09:26 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
13,000
Videos
2,240
Links
6,410

Lifetime counters from Telegram’s own channel header, read 10 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
2h 55m
Average length
39s

Measured directly from 271 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

17,061 reactions across 658 posts, in 9 distinct kinds. The most used accounts for 16.9% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
🔥2,88216.9%
2,85616.7%
🎉2,83916.6%
😁2,83616.6%
👍2,82716.6%
🤩2,81216.5%
🥰70.041%
👎10.006%
👏10.006%

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 658 of the 677 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 17,061 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 677 most recent posts we hold, published 7 August 2026 to 10 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

10 Sept 2026, 09:10 UTC≈1,400 views22 reactionsread 10 September 2026
Video

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10 Sept 2026, 08:56 UTC≈3,000 views27 reactionsread 10 September 2026
Photo

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10 Sept 2026, 06:03 UTC≈6,590 views17 reactionsread 10 September 2026
Video

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10 Sept 2026, 04:20 UTC4 views15 reactionsread 10 September 2026
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10 Sept 2026, 04:19 UTC≈5,370 views14 reactionsread 10 September 2026
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10 Sept 2026, 00:08 UTC≈4,030 views28 reactionsread 10 September 2026
Video

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9 Sept 2026, 18:07 UTC≈5,250 views14 reactionsread 10 September 2026
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9 Sept 2026, 15:09 UTC≈5,300 views18 reactionsread 10 September 2026
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9 Sept 2026, 13:45 UTC≈5,540 views23 reactionsread 10 September 2026
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9 Sept 2026, 13:08 UTC≈9,330 views28 reactionsread 10 September 2026
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9 Sept 2026, 13:08 UTC≈4,710 views12 reactionsread 10 September 2026
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人在国外,管好自己的嘴 出国这些年,见过不少“言多必失”的人。仔细观察起来,他们其实并没有坏心眼,而且有些人的人品相当不错,只是有时候为了逞一时口舌之快,没有管住自己的嘴,才间接影响了自己的生活。 每个成年人都必须明白一件事,那就是,我们说出去的话,是收不回来的。无论后续做了什么补救,影响已经造成了。 如果让我总结,在国外最不该说的三类话,那必须是下面这三种。 首先不该说的是气话。 人在国外,既要赚钱,还要照顾好自己的情绪和生活,压力不是一般的大。有些人遇上什么事情都藏在心里,不会发泄出来。长久下去的后果就是,有时候实在忍不住了,会彻底爆发,说出很多气话。 比如在电话里攻击自己的家人,或者面对忍了很久的同事、朋友,突然恶语相向。 说气话的那一刻,他们觉得压力一下子释放了,但代价却很大。家人之间可能因此产生隔阂,同事和朋友也不会惯着你,觉得你情绪不稳定,最后直接远离你。 第二种不该说的话,就是跟自己无关的是非。

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9 Sept 2026, 13:05 UTC≈6,130 views29 reactionsread 10 September 2026
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Showing the 12 most recent of 677 posts we hold for @HaiBo44. 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 9 September 2026 — this entry's latest reading, not the date you are reading this.

“菲律宾大事件🇵🇭海博新闻资讯” (@HaiBo44), 134,201 subscribers as measured 9 September 2026. Telegram Register, tgregister.com/channel/HaiBo44.

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.