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Channel

斯里兰卡大事件

@sililanka_1

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 · Cite this entry

61,743subscribers

+15,969 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-1003575438542
TypeChannel
Username@sililanka_1
Description#斯里兰卡 #东南亚 #柬埔寨 #菲律宾 #缅甸 #泰国 兰卡华人交流群: @sililanka110 投搞联系: @TG2181 (商务) 斯里兰卡大事件频道专注于东南亚华人最新动态资讯,生活故事分享,海外华人求助,让你看尽海外华人大小事。
CreatedBetween 1 December 2025 and 31 May 2026 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live14 November 2026
Measurements held64
Confirmed unchanged1 time, most recently 14 November 2026
On Telegramt.me/sililanka_1

Topic

National news — 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 47% 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 forms a group of 2 channels linked by matching posts. 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
@baoguangqun01/287618 Aug 2026, 06:06 UTC@sililanka_1/14747 · this entry8 Aug 2026, 06:06 UTC1.00under a minute
@sililanka_1/15155 · this entry12 Aug 2026, 13:46 UTC@baoguangqun01/2917212 Aug 2026, 13:46 UTC1.00under a minute
@baoguangqun01/2921613 Aug 2026, 07:30 UTC@sililanka_1/15204 · this entry13 Aug 2026, 07:30 UTC1.00under a minute
@sililanka_1/15453 · this entry16 Aug 2026, 13:50 UTC@baoguangqun01/2946416 Aug 2026, 13:50 UTC1.00under a minute
@sililanka_1/15894 · this entry22 Aug 2026, 15:53 UTC@baoguangqun01/2988122 Aug 2026, 15:53 UTC1.00under a minute
@baoguangqun01/2991523 Aug 2026, 10:29 UTC@sililanka_1/15930 · this entry23 Aug 2026, 10:29 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
@baoguangqun01406 (8/8 hand-verifiable sample passed)1.00under a minute@baoguangqun01 (329–77)
@baoguangqun11064 (8/8 hand-verifiable sample passed)1.00under a minutethis entry (51–13)
@baoguang_qun51 (8/8 hand-verifiable sample passed)1.00under a minutethis entry (50–1)
@baoguang_9940 (8/8 hand-verifiable sample passed)1.00under a minutethis entry (38–2)
@baoguangqun99925 (8/8 hand-verifiable sample passed)0.98under a minute@baoguangqun999 (13–12)
@JPZJBFBI21 (7/8 hand-verifiable sample passed)1.0025 minutes@JPZJBFBI (16–5)
@hrxw8888816 (6/8 hand-verifiable sample passed)1.0028 hoursthis entry (16–0)
@quanwangdsj14 (8/8 hand-verifiable sample passed)1.0027 minutes@quanwangdsj (10–4)
@baoguangchn13 (8/8 hand-verifiable sample passed)1.0052 minutes@baoguangchn (7–6)
@huisedny12 (8/8 hand-verifiable sample passed)1.0032 minutes@huisedny (8–4)
@sjhrcg10 (7/8 hand-verifiable sample passed)1.0027 hoursthis entry (10–0)
@mrbg88810 (6/8 hand-verifiable sample passed)1.0019 hoursthis entry (10–0)

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. 420 of the 420 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 1,479 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 2 channels, the one whose matching posts we hold earliest is @baoguangqun01. 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 2 registered channels linked by matching posts. 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

12,74965,59739,17361,7437 August 202614 November 2026
64 measurements spanning 99 days, net +15,969. 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 4,822–73,524 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 64
Measured (UTC)SubscribersChange
14 Nov 2026, 17:1661,743-386
11 Nov 2026, 21:0862,129-138
9 Nov 2026, 23:0162,267-162
8 Nov 2026, 12:4662,429-200
7 Nov 2026, 04:2762,629-48
6 Nov 2026, 06:1662,677-38
5 Nov 2026, 01:5762,715-61
4 Nov 2026, 03:1862,776-205
3 Nov 2026, 03:3162,981-208
2 Nov 2026, 00:1663,189-149
31 Oct 2026, 23:1563,338-238
30 Oct 2026, 19:3863,576-263
29 Oct 2026, 16:0963,839-105
28 Oct 2026, 15:1063,944-75
27 Oct 2026, 12:0664,019-51
26 Oct 2026, 10:1664,070-79
25 Oct 2026, 09:1664,149-193
24 Oct 2026, 06:4964,342-99
23 Oct 2026, 03:3564,441-197
22 Oct 2026, 00:2064,638first reading

Engagement

1,808 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 162 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
1.56%
avg views ÷ 61,743 subscribers
Avg views / post
963
670 posts measured
Reaction rate
0.138%
reactions ÷ views · ER floor
Posts in window
748
of 1,808 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 670 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 held1,808 (7 August 2026 – 14 November 2026)
Views total645,143
Reactions total11
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken14 Nov 2026, 23:14 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
≈17,300
Videos
≈2,760
Links
≈4,740

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 22m
Average length
33s

Measured directly from 152 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

13 reactions across 12 posts, in 5 distinct kinds. The most used accounts for 69.2% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤969.2%
⚡17.69%
👍17.69%
👏17.69%
🔥17.69%

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 16 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 13 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 30 September 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: 3 of 748 posts held from the last 30 days (0.401%) 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, 17:14 UTC39 viewsread 14 November 2026
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#马来西亚资讯: #雪兰莪 移民局突击检查三个地点,34名外国人被捕!有人躲床底企图逃避检查 马来西亚雪兰莪州移民局于11月13日展开联合执法行动,突击检查 Kampung Baru Subang、Ampang 及 Hulu Langat 三个地点,共检查38人,并逮捕34名外国人。 据报道,此次行动共出动18名移民局执法人员,涉及 Ops Sapu、Ops Selera 及 Ops Kutip 三项执法行动。 行动期间,执法人员在检查过程中发现,部分外国人试图躲藏在床底等地方,以逃避执法人员检查,但最终仍被发现。 在 Ampang 地区的行动中,共有10名外国人被捕,包括8名缅甸籍、1名印尼籍及1名印度籍人员。此外,Hulu Langat 地区也有一名波兰籍人员落网。 此次行动累计检查38人,逮捕34名外国人。执法部门同时向一名相关人士发出证人传票,并对一名雇主采取行动。 被捕人员涉嫌违反马来西亚《1959/63年…

14 Nov 2026, 16:46 UTC≈2,230 viewsread 14 November 2026
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#菲律宾资讯:警方寻求外国执法机构协助,核查数百名同胞被困缅甸诈骗园区 11月12日,菲律宾媒体报道,菲律宾国家警察(PNP)正与外国执法机构及相关政府部门展开协调,核查数百名菲律宾人疑似被困缅甸诈骗园区的消息,并研究可能的跨国营救方案。 菲律宾国家警察总长 Jose Melencio Nartatez Jr. 表示,警方正在核实有关菲律宾劳工遭非法拘禁的情况,并与相关国家执法部门保持沟通,以确认被困人员的身份、具体位置及案件详情。 此前,菲律宾前反有组织犯罪委员会(PAOCC)官员 Winston Casio 透露,据相关消息估计,目前可能仍有约900至1500名菲律宾人被困在缅甸诈骗园区。其中,部分人员疑似遭到殴打、限制人身自由,甚至被迫参与网络诈骗活动。 目前,菲律宾警方正重点核查人员招募渠道、跨国人口贩卖网络以及相关诈骗组织的运作情况,同时研究后续营救和追责措施。

14 Nov 2026, 16:24 UTC≈2,230 viewsread 14 November 2026
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14 Nov 2026, 16:19 UTC≈2,290 viewsread 14 November 2026
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#美高梅娱乐平台 💵😄😁😂☺️😊🙃😍😭 免实名.放心赢💵 😆😆😆😅😂☺️🙃😉☺️😊😏😀😃😁😆 😀真人、电子、体育、彩票、棋牌、捕鱼😳 😃😄😃😄😃😄😄😄😃😃😄😃 😒😞🙂‍↔️🙂‍🙂‍↔️: 立即注册 😒😞🙂‍↔️🙂🙂‍↔️: 立即注册 😒😞🙂‍↔️🙂🙂‍↔️: 立即注册 ⭐电子每日首存赠送😃😄 🛍 💵充值笔笔赠送😃🛍无上限~! 💶首存100 赠送 20 大礼包,奢华体验! 🪙每日签到送海量彩金,惊喜不断! 💷天天红包抽奖,万元大奖等您抱回家! 💴加入即享额外福利,成为赢家的第一步! 选平台很重要,要选能赢的!😀😀😀 ⚡上⚡下安全可靠无需绑卡! ⚡来⚡去 无需担心传统银行的风险! 🪙新人注册送😒🥰 注:联系美高梅客服即可申请领取 🙂‍↔️十年口碑沉淀,信用成就平台价值🙂‍↔️ 😃😄😃😄😀😃😄 ⭐官方客服:@MGM1791😃 ⭐官方频道:@mgm97188😃 ⭐官方群组:@m971g😃 ⭐官方招商:@mgmzs97

14 Nov 2026, 15:02 UTC≈2,200 viewsread 14 November 2026
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#马来西亚资讯:吉打移民局再遣返137名中国籍人员!4天分两阶段共286人被送回中国,全部列入黑名单 11月13日至14日凌晨,马来西亚吉打州移民局安排6趟航班,通过槟城峇六拜国际机场,将137名中国籍非法移民遣返回中国。 据吉打州移民局11月14日发布的文告,这批被遣返人员全部为成年男性,此前被关押在吉打州锡县柏兰迪移民局扣留营(Belantik Immigration Depot)。 此次是吉打州移民局近期第二阶段遣返行动。此前,11月11日,当局已遣返149名中国籍扣留人员。 短短4天内,吉打州移民局分两个阶段,累计遣返286名中国籍人员。 此次遣返行动的主要情况: 第一阶段: 11月11日,遣返149人。 第二阶段: 11月13日至14日凌晨,遣返137人。 累计人数: 两阶段共286人。 遣返地点: 槟城峇六拜国际机场。 人员情况: 第二阶段137人全部为成年男性。 原关押地点: 吉打州锡县柏兰迪移民局扣留营。…

14 Nov 2026, 14:11 UTC44 viewsread 14 November 2026
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#网友曝光 出轨女 #静静 最近我身边发生好多事情 有兄弟女朋友给他戴绿帽子 还有群里面看见各种各样的曝光说得病 想不到今天会发生在我身上 我只是想问问各位网友们 在这个时代 当你很相信的一个人女生 她给你说她和中国人只是单纯谈恋爱 你相信吗? 事情是这样的 我和她三年多感情了以前她不是那种女生 她对中国人也是反感的 上几个月我把她叫过来亚太 我把她找了一份工作 在二号地寺庙篮楼 1楼 做空降模式的刚开始我们好好的 后面她过去不久 发工资了 和这个中国人去吃了一顿火锅 后面就开始和我各种各样吵 我们在冷战中 我一直问她你是不是在外面喜欢别人了 她说没有她不是那种女人 后面我们吵的很厉害 说我们男人怎么怎么样 男人不是一个好东西 直到11月7号还是8号她叫我去宾馆 我们做了后面我发现她手机飞机聊天记录 我问她那个是谁 她说是朋友 后面说是刚刚谈的男朋友 只是单纯谈恋木有做过什么 搞不搞笑嘛单纯谈恋爱 后面我看了我们之…

14 Nov 2026, 13:23 UTC≈2,220 viewsread 14 November 2026
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曾经福利最高的欧洲真的没落了。 #网友投稿 我朋友老周,在法国生活了十年,上个月拖家带口回来了。我们几个给他接风,本以为他会大谈欧洲多好多好,结果他坐下来第一句是:“以前觉得欧洲福利好是天堂,现在才知道,天堂也要交物业费了,而且越来越贵。” 老周是十年前去的法国,先在里昂读书,后来在巴黎一家物流公司做管理。他说刚去那几年,确实觉得福利不是吹的。看病有医保,报销比例高。孩子上公立学校几乎不花钱。失业了有失业金,虽然不多,但饿不死。每年带薪假五周,八月整个国家都在度假。他那时候给国内朋友打电,语气里全是优越感。 但他说,从第五年开始,感觉一点点变了。 先是看病。以前预约专科医生,等一两周算长的。后来等一个月是常态,有的科室要等三个月。他老婆有次胃疼得厉害,家庭医生看了说没事,开点胃药打发回来了。后来疼得受不了,去急诊,从晚上八点等到凌晨两点才见到医生。医生看完说,你这个得约专科,急诊看不了。他老婆坐在医院走廊里疼得直哭,他站…

14 Nov 2026, 13:22 UTC40 viewsread 14 November 2026
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#网友求助 恳请大家帮忙寻找现在实在没有办法,只能借助广大朋友的力量,希望大家帮忙留意。 这个女孩外号:(云宝、车厘子)在老挝万象 11月9号突然消失,所有联系方式全部失联.亲人、好友,非常担心着急. 如果是被绑了、还是被卖了?如果是要赎金请联系以下小编 如果有哪位朋友见过他本人,或者在老挝、柬埔寨等地有朋友、认识相关人员,能够提供任何线索,烦请第一时间与我联系。哪怕只是一点点消息,对家人来说都非常重要。 在此先感谢每一位愿意帮忙、提供线索的朋友!🙏 PS:真的是人美逼遭罪哎~~

14 Nov 2026, 12:56 UTC≈2,060 viewsread 14 November 2026
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#网友投稿 金边今晚加强安保!独立纪念碑附近也有大批联合执法人员严密巡逻、值守。

14 Nov 2026, 12:38 UTC≈2,050 viewsread 14 November 2026
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#群友投稿:昨晚的老挝万象三江。曾经无限风光,现在人去楼空。 三江国际商贸城,是万象最早成型的华人商圈之一。早年这里依托中老贸易红利,吸引大量国内商户前来淘金,从日用百货、五金批发到餐饮住宿、签证代办,产业链完整。鼎盛阶段,这里汇聚上万华人,普通话通行、人民币直接结算,被大家称作万象的“中国城”,是很多人奔赴东南亚的第一站。 潮水慢慢转向,跨境电诈、非法居留问题集中爆发,老挝警方多次针对三江片区开展大规模清查抓捕行动,大批涉案人员被带走、遣返。依附人流生存的餐饮、酒店、娱乐配套跟着失去客源,大量店铺转让、关门,租客陆续搬走。 如今再走进三江,宽阔的街道不再拥堵,曾经一房难求的公寓大量空置,许多招牌还挂着中文,门内却早已人去铺空。 湄公河畔的淘金梦,起于商贸,也乱于灰产。曾经彻夜不息的热闹,一夜之间归于沉寂,只剩空荡的街区,记录着东南亚华人圈子一场来去匆匆的起落。

14 Nov 2026, 12:37 UTC35 viewsread 14 November 2026
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#网友投稿 Permission to post, Admin. I’m hoping someone in this group knows NIKKI JANE BERBANO, also known as “FIONA,” as she has been unreachable and nowhere to be found. I would really appreciate any help in getting in touch with her. Thank you. I am not posting this to humiliate or embarrass anyone. I am calling her out because I have tried all possible ways of contacting her, and unfortunately, she remains unreach…

14 Nov 2026, 11:05 UTC315 viewsread 14 November 2026
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#泰国新闻 芭堤雅抓获台湾籍通缉犯,身负15项通缉涉谋杀、洗钱及诈骗7000万泰铢 11月13日报道,泰国警方近日在春武里府芭堤雅展开抓捕行动,成功逮捕一名50岁台湾籍男子 Teng Chi Chen。该男子在台湾身负15项通缉,涉及1起谋杀案、1起洗钱案以及13起诈骗案,涉嫌诈骗金额超过7000万泰铢。 据报道,嫌疑人此前逃往泰国,并将旅游签证转换为退休签证,长期在当地居留。期间,他还与两名泰国合伙人共同成立一家珠宝公司,并担任公司董事。 根据台湾方面提供的线索,驻泰台北经济文化办事处向泰国旅游警察通报相关情况。泰国警方随后锁定嫌疑人藏匿于春武里府芭堤雅邦拉蒙县农普鲁地区。 当地移民局先行撤销其签证,并联合旅游警察展开抓捕部署。11月12日下午5时许,嫌疑人走出住所时被警方当场逮捕。 警方目前正在调查其名下珠宝公司的银行账户及资金往来,排查是否存在利用公司转移犯罪所得的情况。不过,截至目前,尚未发现该公司与台湾方面的相…

Showing the 12 most recent of 1,808 posts we hold for @sililanka_1. 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 14 November 2026 — this entry's latest reading, not the date you are reading this.

“斯里兰卡大事件” (@sililanka_1), 61,743 subscribers as measured 14 November 2026. Telegram Register, tgregister.com/channel/sililanka_1.

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.