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Channel

斯里兰卡大事件

@sililanka_1

On this record: Topic · Observations · Also posting the same content · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Handles named that no longer answer · Cite this entry

28,085subscribers

-17,689 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 10,000–31,623.

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 live26 September 2026
Measurements held34
Confirmed unchanged1 time, most recently 26 September 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 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
@sililanka_1/14710 · this entry7 Aug 2026, 14:26 UTC@baoguangqun01/287237 Aug 2026, 14:26 UTC1.00under a minute
@sililanka_1/14715 · this entry7 Aug 2026, 14:40 UTC@baoguangqun01/287287 Aug 2026, 14:40 UTC1.00under a minute
@sililanka_1/14721 · this entry7 Aug 2026, 15:02 UTC@baoguangqun01/287347 Aug 2026, 15:02 UTC1.00under a minute
@sililanka_1/14724 · this entry7 Aug 2026, 15:19 UTC@baoguangqun01/287357 Aug 2026, 15:19 UTC1.00under a minute
@sililanka_1/14725 · this entry7 Aug 2026, 15:44 UTC@baoguangqun01/287367 Aug 2026, 15:44 UTC1.00under a minute
@baoguangqun01/287397 Aug 2026, 16:07 UTC@sililanka_1/14726 · this entry7 Aug 2026, 16:07 UTC1.00under a minute
Every channel this entry shares post bodies with
ChannelMatching postsText overlapTypical gapPublished first
@baoguangqun019 (8/8 hand-verifiable sample passed)1.00under a minute@baoguangqun01 (8–1)

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. 8 of the 8 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 10 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 @baoguangqun01. That is a statement about our reading window, not a claim of authorship.

Recorded under the key clone_copy, last confirmed 7 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

28,08545,77436,929.57 August 2026 — 45,774 subscribers7 August 2026 — 45,774 subscribers7 August 2026 — 45,645 subscribers9 August 2026 — 45,268 subscribers10 August 2026 — 44,846 subscribers10 August 2026 — 44,555 subscribers12 August 2026 — 44,104 subscribers13 August 2026 — 43,777 subscribers14 August 2026 — 43,152 subscribers15 August 2026 — 42,549 subscribers17 August 2026 — 42,014 subscribers18 August 2026 — 41,634 subscribers19 August 2026 — 41,446 subscribers20 August 2026 — 41,288 subscribers21 August 2026 — 40,787 subscribers23 August 2026 — 36,530 subscribers24 August 2026 — 33,967 subscribers26 August 2026 — 33,773 subscribers27 August 2026 — 33,622 subscribers28 August 2026 — 33,363 subscribers29 August 2026 — 33,018 subscribers29 August 2026 — 32,591 subscribers30 August 2026 — 32,447 subscribers31 August 2026 — 32,360 subscribers1 September 2026 — 32,160 subscribers2 September 2026 — 32,003 subscribers4 September 2026 — 31,882 subscribers6 September 2026 — 31,697 subscribers9 September 2026 — 31,248 subscribers12 September 2026 — 30,706 subscribers13 September 2026 — 30,199 subscribers15 September 2026 — 29,834 subscribers17 September 2026 — 29,638 subscribers26 September 2026 — 28,085 subscribers7 August 202626 September 2026
34 measurements spanning 50 days, net -17,689. 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 25,432–48,427 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 34
Measured (UTC)SubscribersChange
26 Sept 2026, 14:4128,085-1,553
17 Sept 2026, 09:1929,638-196
15 Sept 2026, 09:3829,834-365
13 Sept 2026, 20:1930,199-507
12 Sept 2026, 03:3630,706-542
9 Sept 2026, 18:5731,248-449
6 Sept 2026, 11:3931,697-185
4 Sept 2026, 04:2031,882-121
2 Sept 2026, 21:2732,003-157
1 Sept 2026, 20:0632,160-200
31 Aug 2026, 18:5732,360-87
30 Aug 2026, 18:2632,447-144
29 Aug 2026, 21:3832,591-427
29 Aug 2026, 00:2433,018-345
28 Aug 2026, 00:0433,363-259
27 Aug 2026, 03:0633,622-151
26 Aug 2026, 01:3233,773-194
24 Aug 2026, 23:1833,967-2,563
23 Aug 2026, 11:5336,530-4,257
21 Aug 2026, 20:3440,787first reading

Engagement

729 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 74 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
3.01%
avg views ÷ 28,085 subscribers
Avg views / post
846
239 posts measured
Reaction rate
0.158%
reactions ÷ views · ER floor
Posts in window
274
of 729 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 12 of 239 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 27 September 2026
Posts held729 (7 August 2026 – 27 September 2026)
Views total202,175
Reactions total12
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken27 Sept 2026, 07:36 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
≈14,400
Videos
≈2,400
Links
≈4,720

Lifetime counters from Telegram’s own channel header, read 27 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 28m
Average length
29s

Measured directly from 180 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

28 reactions across 28 posts, in 4 distinct kinds. The most used accounts for 78.6% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤2278.6%
👍414.3%
🤣13.57%
🥰13.57%

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 30 of the 729 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 28 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 729 most recent posts we hold, published 7 August 2026 to 27 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

27 Sept 2026, 07:16 UTC≈1,520 views1 reactionsread 27 September 2026
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#群友投稿:新型盗U,兄弟们注意了! 骗子找到了新套路:不发钓鱼链接,诱导用户主动清空自己的钱包。他们在 YouTube 上传教程,教大家用 Claude 搭建 AI 加密货币交易机器人。 最近出现一种全新的虚拟币骗局,和以往发钓鱼链接骗密码的套路完全不一样,全程没有钓鱼链接,而是引导受害者亲手操作,自己把钱包里的资产转给骗子。 骗子在 YouTube 大量发布视频教程,用 AI 生成虚拟主播配音,对外宣称:可以借助 Claude 大模型,一键搭建自动套利的加密货币交易机器人,开启之后自动赚钱,稳赚不赔。 骗局完整流程 1. 视频里演示全套教程,教观众复制代码,去一个仿冒的合约编译网站部署智能合约,看起来非常专业。 2. 这个编译网站是骗子自己搭建的,你粘贴进去的正常代码会在后台偷偷替换成盗币代码。屏幕上展示的代码是干净的,实际部署到链上的是盗币合约。 3. 按照视频指引,受害者自己把加密货币转入合约钱包,手动确认授…

❤1

27 Sept 2026, 06:53 UTC≈1,530 viewsread 27 September 2026
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菲妹向中国男友要彩礼,遭逮捕! 据菲国警首都区警察署(NCRPO)通报,9月26日,帕赛市警方逮捕一名23岁菲律宾女子,该女子涉嫌以索要“彩礼”为名,多次向中国籍男友索要钱财,最终对方选择报警处理。 据帕赛市警察局记录,报案人是一名从事货币兑换生意的30岁中国籍男子。他此前以为两人是在认真谈恋爱,先后以“求父母祝福”为由,被女子索走共计13万比索的“彩礼”。 女子随后变本加厉,要求他拿出20万比索现金给其父母过目,以证明养得起这段感情。当女子在凌晨再次开口索要1万比索时,受害人才识破骗局,随即报警求助。 警方接报后迅速以标记货币策划诱捕行动。女子接过1万比索“标记钞票”后即被当场逮捕,警方并从其身上搜出手机一部。然而现场却出现意外一幕:一名29岁菲律宾男子试图协助女子脱身逃跑,结果被警方一并当场拿下,不过通报中并未提及该男子与被捕女子的关系。 目前,涉案女子面临诈骗罪指控,另一名男子被控妨碍司法罪。

27 Sept 2026, 06:47 UTC≈1,530 viewsread 27 September 2026
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中国女主播被诱骗前往泰国,后遭绑架转移至缅甸,勒索9万美元赎金 27日,据《南华早报》报道,一名中国网络带货主播 Wang Ran 被指在缅甸遭到非法拘禁,对方索要 9万美元赎金。 据中国官方媒体报道,Wang Ran 最初被熟人以工作为由诱骗前往泰国,之后她告诉朋友,自己被强行控制在缅甸。 家属表示,现年24岁的 Wang Ran 遭人扣押,对方要求支付 60万元人民币(约9万美元)赎金。据称,她此前是被一名通过网络认识的人以“工作机会”为由骗去泰国的。 这也是近期又一起中国网络主播以“海外工作”为诱饵,被骗前往东南亚诈骗园区的案件。

27 Sept 2026, 06:12 UTC≈1,540 viewsread 27 September 2026
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#网友爆料:柬埔寨/磅湛7号园区/三期三号地/三楼黑公司!2025年 大老板:“欢啊”,是福建省泉州市安溪县湖头镇福什么村?你们自己知道!二老板:“毕啊”(福建人,福建省泉州市安溪县湖头镇什么车,你们自己知道。后勤:“大七”,也是泉州安溪湖头。精聊大主管:“阿峰”,福建省泉州市安溪县湖头镇福村。 园区里面食堂老板,外号叫“阿平”,小名叫“啊炮”,福建省泉州市安溪县湖头镇现产贤堂。这个公司是做美国精聊和国内色粉的,无恶不作,涉及买卖人口,打人只是家常便饭,电棍高压! 我是当时在你们公司遭受霸凌的众多受害者之一,你们知道我是谁。我也知道你们住在马来西亚哪里。你之前泰国的别墅也被封掉,限你们三天内出来给我一个说法,不然全部爆出来!

27 Sept 2026, 05:52 UTC34 viewsread 27 September 2026
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#群友吐槽: 这两个逼养的玩仙人跳 找了一个15岁的女孩说一起玩 然后说给我安排。 我就给这两个逼开了一个房间。 那个女孩就在我房间。 各种暗示我。然后我干完了后。马上就有人敲门了。然后这个女的跑的很快就去把门打开了。 然后就气冲冲的冲进来三个男的说我干她女朋友。然后就敲诈我。还录视频。我本来不想射里面的。这个逼养的女的我要射的时候抱的很紧。后面才发觉是想留下证据好敲诈我。 他们应该玩仙人跳很久了。 带头的就是这个郑斌斌。我现在有点担心这女的有没有病。估计也敲诈过老头。 PS:就当嫖个娼吧~~~都无套内射了 多多少少还是要给点打胎费的

27 Sept 2026, 05:39 UTC26 viewsread 27 September 2026
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西港一女子从8楼跳下 奇迹生还! #网友投稿:今(26日)晚11时40分,西港一名女子从8楼一跃而下,跌落在一栋私人住宅的铁皮屋顶上,奇迹幸存,就问你们牛逼不牛逼,硬不硬! ps:不知道有没有把她摔醒

27 Sept 2026, 05:23 UTC29 viewsread 27 September 2026
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#网友投稿 #金羽 此人叫 金羽 飞机名字叫 羽 长期活跃在西港人才聚集地群 刚刚开始合作的时候给我核销卡好好的 后面因为相信他给他大额跑分 从头到尾全程都是空放给他 想着都是兄弟 长期合作 2026年9月17号给他空放50万台币 合计10500U转进去一分钟没有就说户死了 叫他提供相关资料老是逃避 无法提供任何证明 当初合作的时候说好的当天回款 这笔钱进去了以后就开始耍赖 在催他以后给我下发6000u 现在还差4500u 消息不回 群里两个号都是他的 还说是客服 客服可以几天不在线 他一出现客服就出现了 把我当猴耍 还说从缅甸到越南什么过境什么 我想请问缅甸到越南需要3天? 期间叫他下发 不是说他客服被抓 叫他提供客服信息我去帮他查也不提供 动不动说几十万 现在维护期过了 还差4500u都不下发 扯东扯西的 见过不要见的没见过这么不要脸的 群里说马上结清 几万几万的截图都是假图 只是我不想说你 给你留面子 说什么客服被抓…

27 Sept 2026, 05:01 UTC34 viewsread 27 September 2026
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#网友吐槽 #麻将胡了2 摇麻将胡了2, 2个号5天输了差不多30万,一点起伏都没,上去就是死.基本摇的是120到240一下的,要么5.6百把不进去一下,要么进去摇大奖给2000.3000,真他妈离谱200一摇,来3个胡进去摇大奖长期给2000多,有的时候给几百,甚至空转,完了几年的平台了,最近回来又转了下电子,没想到PG电子已经这么没底线了,原来我也没少输,最起码原来有起伏,这只要充值,上去分数就是在掉,纯杀猪

26 Sept 2026, 16:19 UTC≈2,490 viewsread 26 September 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😳 😃😄😃😄😃😄😄😄😃😃😄😃 😒😞🙂‍↔️🙂‍🙂‍↔️: 78xu.vip 😒😞🙂‍↔️🙂🙂‍↔️: 78xu.vip 😒😞🙂‍↔️🙂🙂‍↔️: 78xu.vip ⭐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

26 Sept 2026, 15:45 UTC≈2,710 viewsread 26 September 2026
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#网友投稿:太子集团某大哥在加拿大被绑架了一个多月,付了3000W赎金放出来了,据说这名大哥姓dai

26 Sept 2026, 14:51 UTC28 viewsread 26 September 2026
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#群友求助 #繁花糖水铺 身高:155cm 走失时间:2026年 9 月 21 日下午 走失地点:老挝万象三江中国城附近 据她本人描述跟两个女孩子去老挝万象考察项目想做点小生意之类的,其中一个女孩子据她说叫雅雅(图一为雅雅飞机)据其他人告诉可能还有一个男生叫左左(小左图二图三)也跟她在一起。 家里人非常的着急,如有具体关于她同行人或知道她在老挝情况的请联系,拜托帮忙转发🙏

26 Sept 2026, 14:06 UTC≈1,700 viewsread 26 September 2026
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#马来西亚 中国男子航班上偷钱包未遂!被罚3000令吉⚠️ 9月25日,马来西亚槟城一名55岁中国籍男子因涉嫌在从印度尼西亚飞往槟城的航班上偷窃乘客钱包,被带上推事庭受审。 控方指控,陈帮军于9月17日在航班上企图从一名男子的背包内偷走钱包,但最终未能得手。案件援引马来西亚《刑事法典》第379条及第511条处理。被告通过中文翻译听取控状后当庭认罪。 辩方求情称,被告目前没有工作,羁押期间已经反省,且案件属于偷窃未遂,并未造成实际财物损失。 法庭最终判处他罚款3000令吉,若无法缴清,则以3个月监禁替代。

Showing the 12 most recent of 729 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 26 September 2026 — this entry's latest reading, not the date you are reading this.

“斯里兰卡大事件” (@sililanka_1), 28,085 subscribers as measured 26 September 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.