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Channel

泰国大事件

@qiusu664

On this record: Topic · Observations · Channels linked by matching posts · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Handles named that no longer answer · Telegram's recommendations · Cite this entry

46,159subscribers

-5,188 since we began measuring on 14 August 2026

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

Register entry

Telegram ID-1001407037645
TypeChannel
Username@qiusu664
Description本频道推送每日曝料,精选内容,仅供观看,真假自辨。 商务合作: @dnysvip 新闻自动投稿: @xinwentougaobot
CreatedBetween 1 March 2019 and 31 October 2021 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded14 August 2026
Last confirmed live14 November 2026
Measurements held58
Confirmed unchanged1 time, most recently 14 November 2026
On Telegramt.me/qiusu664

Topic

National news — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 9 September 2026 and assigned it the closest of 31 fixed categories, at 98% 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 9 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
@xinwenriji/8206613 Aug 2026, 15:21 UTC@qiusu664/73210 · this entry13 Aug 2026, 15:47 UTC1.0026 minutes
@xinwenriji/8250517 Aug 2026, 10:27 UTC@qiusu664/73731 · this entry17 Aug 2026, 10:54 UTC1.0027 minutes
@xinwenriji/8312322 Aug 2026, 12:26 UTC@qiusu664/74451 · this entry22 Aug 2026, 12:54 UTC1.0028 minutes
@xinwenriji/9070631 Oct 2026, 10:19 UTC@qiusu664/82246 · this entry31 Oct 2026, 10:48 UTC1.0029 minutes
@qiusu664/83207 · this entry10 Nov 2026, 10:04 UTC@xinwenriji/9177210 Nov 2026, 10:06 UTC1.002 minutes
@qiusu664/83304 · this entry11 Nov 2026, 11:17 UTC@xinwenriji/9187411 Nov 2026, 11:20 UTC1.002 minutes
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
@xinwenriji528 (7/8 hand-verifiable sample passed)1.004 minutesthis entry (301–227)
@ershouflb349 (7/8 hand-verifiable sample passed)1.0043 minutesthis entry (327–22)
@sucaidny282 (8/8 hand-verifiable sample passed)1.0016 minutesthis entry (269–13)
@chiguabgt223 (8/8 hand-verifiable sample passed)1.0061 minutes@chiguabgt (219–4)
@ZFJCG156 (8/8 hand-verifiable sample passed)1.003.2 hours@ZFJCG (156–0)
@PG681132 (8/8 hand-verifiable sample passed)1.001.6 hours@PG681 (114–18)
@jpz9188131 (8/8 hand-verifiable sample passed)1.0079 minutes@jpz9188 (117–14)
@baoguang82198 (8/8 hand-verifiable sample passed)0.9545 minutes@baoguang821 (77–21)
@wmxw868780 (7/8 hand-verifiable sample passed)1.0046 minutesthis entry (68–12)
@xinwenbaoguang0052 (8/8 hand-verifiable sample passed)0.982.5 hours@xinwenbaoguang00 (51–1)
@MTGBG30 (7/8 hand-verifiable sample passed)1.002.1 hours@MTGBG (30–0)
@dubaixinwen229 (8/8 hand-verifiable sample passed)1.004.5 hours@dubaixinwen2 (24–5)

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. 1,236 of the 1,236 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 1,795 comparable posts for this entry, running 13 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 9 channels, the one whose matching posts we hold earliest is @PG681. 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 9 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

46,15956,30151,23014 August 2026 — 51,347 subscribers15 August 2026 — 51,279 subscribers16 August 2026 — 51,020 subscribers17 August 2026 — 50,809 subscribers18 August 2026 — 50,709 subscribers19 August 2026 — 50,648 subscribers20 August 2026 — 50,567 subscribers21 August 2026 — 50,503 subscribers23 August 2026 — 50,214 subscribers24 August 2026 — 55,124 subscribers25 August 2026 — 56,301 subscribers26 August 2026 — 56,107 subscribers28 August 2026 — 56,069 subscribers29 August 2026 — 55,930 subscribers30 August 2026 — 55,881 subscribers31 August 2026 — 55,657 subscribers1 September 2026 — 55,591 subscribers2 September 2026 — 55,463 subscribers3 September 2026 — 55,262 subscribers5 September 2026 — 55,110 subscribers9 September 2026 — 54,751 subscribers11 September 2026 — 53,903 subscribers13 September 2026 — 53,154 subscribers15 September 2026 — 52,973 subscribers17 September 2026 — 52,763 subscribers19 September 2026 — 52,646 subscribers27 September 2026 — 52,154 subscribers4 October 2026 — 51,252 subscribers9 October 2026 — 50,350 subscribers13 October 2026 — 50,122 subscribers14 October 2026 — 50,041 subscribers15 October 2026 — 49,839 subscribers16 October 2026 — 49,663 subscribers17 October 2026 — 49,455 subscribers18 October 2026 — 49,333 subscribers19 October 2026 — 49,285 subscribers20 October 2026 — 49,239 subscribers22 October 2026 — 49,166 subscribers23 October 2026 — 49,108 subscribers24 October 2026 — 49,031 subscribers24 October 2026 — 48,892 subscribers25 October 2026 — 48,817 subscribers27 October 2026 — 48,746 subscribers28 October 2026 — 48,648 subscribers29 October 2026 — 48,542 subscribers30 October 2026 — 48,254 subscribers31 October 2026 — 48,119 subscribers1 November 2026 — 48,014 subscribers2 November 2026 — 47,920 subscribers3 November 2026 — 47,623 subscribers4 November 2026 — 47,392 subscribers5 November 2026 — 47,304 subscribers6 November 2026 — 47,229 subscribers7 November 2026 — 47,114 subscribers8 November 2026 — 47,003 subscribers9 November 2026 — 46,804 subscribers11 November 2026 — 46,650 subscribers14 November 2026 — 46,159 subscribers14 August 202614 November 2026
58 measurements spanning 92 days, net -5,188. 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 44,638–57,822 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 58
Measured (UTC)SubscribersChange
14 Nov 2026, 10:0746,159-491
11 Nov 2026, 15:3846,650-154
9 Nov 2026, 19:4146,804-199
8 Nov 2026, 10:0647,003-111
7 Nov 2026, 07:5847,114-115
6 Nov 2026, 07:2847,229-75
5 Nov 2026, 04:0047,304-88
4 Nov 2026, 04:3047,392-231
3 Nov 2026, 04:0947,623-297
2 Nov 2026, 05:1047,920-94
1 Nov 2026, 06:3948,014-105
31 Oct 2026, 09:3448,119-135
30 Oct 2026, 07:5648,254-288
29 Oct 2026, 09:4648,542-106
28 Oct 2026, 06:0948,648-98
27 Oct 2026, 02:5948,746-71
25 Oct 2026, 23:5548,817-75
24 Oct 2026, 22:3648,892-139
24 Oct 2026, 01:0949,031-77
23 Oct 2026, 00:3849,108first reading

Engagement

2,496 posts held, back to 13 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 184 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
0.704%
avg views ÷ 46,159 subscribers
Avg views / post
325
746 posts measured
Reaction rate
0.214%
reactions ÷ views · ER floor
Posts in window
869
of 2,496 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 17 of 746 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 held2,496 (13 August 2026 – 14 November 2026)
Views total242,250
Reactions total17
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken15 Nov 2026, 00:18 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
≈43,100
Videos
≈17,800
Links
≈133

Lifetime counters from Telegram’s own channel header, read 15 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 55m
Average length
25s

Measured directly from 281 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 reactions across 17 posts, in 1 kind.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
👍17100.0%

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 17 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 17 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 10 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 869 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, 17:00 UTC540 viewsread 15 November 2026
Video

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14 Nov 2026, 16:05 UTC610 views1 reactionsread 15 November 2026
Photo

#泰国新闻 【正大集团联手泰国啤酒巨头布局酒类业务】 2026年11月14日,正大集团与泰国啤酒巨头达成合作,酒类业务再落一子。此前,正大旗下正大饮用水公司于2022年因业务发展需要更名为正大饮品(北京)有限公司。2023年9月,正大集团举办饮品新品发布会,推出所以润天然矿泉水、茶椿里等产品。此次联手泰国啤酒巨头,意味着正大在饮品及酒类领域的布局进一步扩展。

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14 Nov 2026, 15:50 UTC561 views1 reactionsread 15 November 2026
Photo

#国际资讯:朝鲜黑客冒充熟人实施视频诈骗,18个月盗走超4亿美元。 11月12日,美国联邦调查局(FBI)与司法部宣布,已采取行动破坏朝鲜黑客组织使用的网络犯罪基础设施。相关攻击活动在过去18个月内窃取超过4亿美元加密货币,FBI还查获了900多段受害者的摄像头录像。 FBI将这套攻击手法称为 “FaceStealer(盗脸者)”,并将相关活动归因于朝鲜黑客组织 Sapphire Sleet(UNC1069)。 攻击通常分为几个步骤: 1.盗取熟人账号: 黑客先入侵受害者的社交媒体或通讯账号,再利用这些账号向其联系人发送视频会议邀请。 2.伪造视频会议: 受害者进入仿冒Zoom、Microsoft Teams或Google Meet的页面后,看到的可能是熟人此前被秘密录制的视频,部分场景还会使用AI深度伪造。 3.制造技术故障: 黑客谎称麦克风或音频出现问题,诱导受害者点击所谓的修复链接或执行操作。 4.植入恶意软…

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14 Nov 2026, 15:48 UTC560 views1 reactionsread 15 November 2026
Video

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14 Nov 2026, 15:34 UTC5 views1 reactionsread 15 November 2026
Video

#吉隆坡 多家夜店突遭检查:26 名女生被带走,无证居留或被列入黑名单 群友投稿:近日吉隆坡Mad Club遭突击检查,26 名女生被带走问话,部分当日获释,其余须等周一办理释放。同老板的Kung Fu 夜店受关注;蒲种Club26亦被移民局核查。

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14 Nov 2026, 15:22 UTC6 views1 reactionsread 15 November 2026
Photo

因快递送餐碰到一个顶美。 没想到网友个个都是变态的 福尔摩斯。

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14 Nov 2026, 15:02 UTC582 views1 reactionsread 15 November 2026
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#泰国新闻 【芭提雅市中心废弃水池现巨蟒 动用挖掘机围捕】 2026年11月14日18时,芭提雅消防部门接报称,春武里府邦拉蒙县农普鲁镇一处约2莱空地上,一名30岁女子在雇挖掘机平整土地准备种菜时,于水池中发现一条腿粗、长逾5米的大蟒蛇。消防人员到场搜寻30多分钟未果,遂让挖掘机搅动水面驱赶,最终在池边将蟒蛇捕获。经查为雌性蟒蛇,重逾30公斤,仅有轻微擦伤,已被放归远离社区的自然区域;挖掘机司机称池中还有约2至3条大蟒蛇。

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14 Nov 2026, 15:00 UTC540 views1 reactionsread 15 November 2026
Video

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14 Nov 2026, 14:48 UTC6 viewsread 15 November 2026
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🇲🇾马来西亚移民局:今年6195人因涉及非法经营活动被捕,印尼籍人数最多 11月14日报道,马来西亚移民局持续加强全国执法行动。移民局总监扎卡里亚表示,截至2026年10月15日,全国已有6195人因涉及非法经营活动被逮捕,其中印尼籍人士占最多,共2280人。 根据移民局公布的数据,被捕人员的国籍分布如下: 印尼籍:2280人 缅甸籍:1742人 孟加拉籍:936人 泰国籍:761人 印度籍:476人 此外,移民局联合地方政府展开216次执法行动,期间共检查3387名外国人,并逮捕487名非法移民及11名雇主。 移民局指出,目前全国已确认224个非法移民聚集热点,其中29个被列为红色高风险区域,分布在全国12个州属。 当局表示,未来将继续加强与地方政府的合作,针对非法移民聚集区域及涉嫌非法经营活动的场所展开执法,以遏制非法经营和移民违法问题。

14 Nov 2026, 14:34 UTC554 viewsread 15 November 2026
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缅甸土瓦东部坡莱矿区限制居民进入,近百名中国公民在当地活动 据当地居民消息,缅甸土瓦东部兴达村附近的坡莱矿区近期出现近百名中国公民居住及作业的情况。当地居民称,该矿区目前禁止普通居民进入,现场由克伦民族联盟(KNU)武装人员负责安保。 据称,这批中国公民持有中缅双重身份证件,从土瓦方向乘车抵达当地,并在矿区附近新建建筑物。当地居民怀疑,相关建筑可能用于筹备诈骗活动及赌场,但目前尚无独立证据证实这一说法。 此外,土瓦东部及甘保地区也有中国公民从事矿产开采和交易活动。当地消息称,部分矿产经泰国转运至中国。 目前,关于坡莱矿区内中国公民的具体身份、实际经营项目,以及是否涉及网络诈骗或赌场活动,仍有待进一步核实。

Showing the 12 most recent of 2,496 posts we hold for @qiusu664. 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.

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.

东南亚大事件(吃瓜)
@HH9915 · 137,937
#1
曝光大事件
@qiusu16 · 675
#2
菲律宾曝光平台
@feilvbinbaogua · 141
#3
最前线大事件曝光
@cctv_dy · 21,008
#4
安危事件
@anwei2 · 31,596
#5
东南亚吃瓜🍉
@dny1577 · 4,980
#6
素材吖
@sucaiya8861 · 560
#7
迪拜新闻|东南亚大事件|曝光群
@baoguang032 · 28,524
#8
🦄奇闻趣事 吃瓜新闻
@n12345 · 1,693
#9
大陆|热点|新闻|吃瓜
@regua_cn · 346
#10
菲律宾新闻|华人资讯曝光|philippine news
@feilvbinhuarenzixun · 67,095
#11
东南亚头条大事件
@tp111 · 50,268
#12
吃瓜丨摸鱼丨内涵段子丨搞笑视频
@chiguagaoxiao12 · 247
#13
菲律宾头条爆料(Bole新闻)
@phnews · 17,003
#14
柬埔寨大事件🇰🇭西港日记
@xinwenhc · 172,980
#15
东南亚热点资讯
@rdzx0 · 86,167
#16
缅甸缅北新闻头条
@chiguaqunzhong_c · 3,302
#17
东南亚新闻(吃瓜)
@jpz9188 · 28,905
#18
菲律宾/头条事件/曝光
@vjtyd · 51,285
#19
中文段子吃瓜中心
@chiguale8 · 48,100
#20
东南亚🇨🇿今日头条
@huohu158 · 170,397
#21
斯里兰卡头条新闻曝光
@baoguangee · 197,174
#22
东南亚新闻|华人资讯曝光|news
@huaren_zixun · 81,569
#23
菲龙网新闻中文媒体【官方】
@feilongwang · 66,826
#24
曝光新闻/全民曝光/独家曝光
@mianbeiy · 59,814
#25
菲律宾华人事件
@feilvbinghuarenriji · 13,872
#26
陆發匯兌官方頻道
@lufa61888 · 3,039
#27
华讯国际新闻News
@huaxuncnn · 909
#28
博彩新闻/今日头条/东南亚新闻
@xinhuaribao · 902
#29
အောင်နိမိတ် မူရင်း အစစ်
@paingzaykhant12345 · 2,415
#30

Read from Telegram’s recommendation API, most recently 24 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.

东南亚大事件(吃瓜)
@HH9915 · 137,937
Telegram ranks this channel #21 of 73 here — alongside 72 others — read 14 August 2026
华人便民大事件-柬搜新闻កម្ពុជា។🇰🇭
@bgyq555 · 51,434
Telegram ranks this channel #29 of 43 here — alongside 42 others — read 23 August 2026

This channel appears in 2 seed channels' Telegram-generated recommendation lists in total. 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 14 November 2026 — this entry's latest reading, not the date you are reading this.

“泰国大事件” (@qiusu664), 46,159 subscribers as measured 14 November 2026. Telegram Register, tgregister.com/channel/qiusu664.

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.