泰国彭世洛33岁大学保安诱骗74岁老妇进树林性侵,已落网 泰国彭世洛府警方11月7日通报,当地一名33岁男子在受害老妇住宅附近搭讪,以邀约外出用餐为借口哄骗74岁老妇坐上摩托车,却将其带至楠河沿岸偏僻树林实施性侵,事后独自骑车折返。警方调取沿线监控锁定嫌疑人,迅速抓捕。落网男子为当地一所大学在职保安,对犯罪供认不讳,辩称情绪失控无法自控。 办案人员已带其到案发树林指认取证,男子以涉嫌强奸罪移交专项调查人员。受害老妇家属强烈呼吁司法部门从严从重惩处。
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Channel
@DNY88880
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Posts recorded as deleted · Citations · Telegram's recommendations · Cite this entry
100,312subscribers
+25,258 since we began measuring on 11 August 2026
Risers and fallers across the register · movement among entries of 100,000–316,228.
| Telegram ID | -1001719628697 |
|---|---|
| Type | Channel |
| Username | @DNY88880 |
| Description | 东南亚华人大事件:@DNY88880 投稿爆料合作: @Fy87781 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。 #东南亚 #柬埔寨 #菲律宾 #缅甸 #泰国 |
| Created | Between 1 December 2021 and 30 April 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 11 August 2026 |
| Last confirmed live | 7 November 2026 |
| Measurements held | 58 |
| Confirmed unchanged | 1 time, most recently 7 November 2026 |
| On Telegram | t.me/DNY88880 |
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 83% 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.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 7 Nov 2026, 14:10 | 100,312 | -420 |
| 6 Nov 2026, 14:54 | 100,732 | +191 |
| 5 Nov 2026, 13:26 | 100,541 | +230 |
| 4 Nov 2026, 16:28 | 100,311 | +175 |
| 3 Nov 2026, 19:37 | 100,136 | -50 |
| 2 Nov 2026, 20:31 | 100,186 | -446 |
| 1 Nov 2026, 23:36 | 100,632 | -2,718 |
| 1 Nov 2026, 02:38 | 103,350 | -171 |
| 31 Oct 2026, 04:57 | 103,521 | -76 |
| 30 Oct 2026, 02:51 | 103,597 | +4 |
| 29 Oct 2026, 04:19 | 103,593 | -127 |
| 27 Oct 2026, 23:59 | 103,720 | +338 |
| 27 Oct 2026, 02:07 | 103,382 | +135 |
| 26 Oct 2026, 04:40 | 103,247 | +163 |
| 25 Oct 2026, 05:47 | 103,084 | +282 |
| 24 Oct 2026, 09:18 | 102,802 | +68 |
| 23 Oct 2026, 09:41 | 102,734 | -370 |
| 22 Oct 2026, 09:54 | 103,104 | +421 |
| 21 Oct 2026, 00:29 | 102,683 | +85 |
| 19 Oct 2026, 20:17 | 102,598 | first reading |
1,222 posts held, back to 10 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 190 pages of Telegram’s post history, 20 posts per page.
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 360 of 380 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 8 November 2026 |
|---|---|
| Posts held | 1,222 (10 August 2026 – 8 November 2026) |
| Views total | 1,213,970 |
| Reactions total | 3,924 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 8 Nov 2026, 08:14 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.
Lifetime counters from Telegram’s own channel header, read 8 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.
Measured directly from 393 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.
8,177 reactions across 890 posts, in 15 distinct kinds. The most used accounts for 14.3% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 👍 | 1,167 | 14.3% | |
| ❤ | 1,027 | 12.6% | |
| 🔥 | 928 | 11.3% | |
| 🎉 | 888 | 10.9% | |
| 🥰 | 803 | 9.82% | |
| 💯 | 796 | 9.73% | |
| 🤩 | 762 | 9.32% | |
| 😍 | 704 | 8.61% | |
| ❤🔥 | 663 | 8.11% | |
| 🙏 | 114 | 1.39% | |
| 👏 | 80 | 0.978% | |
| 😁 | 79 | 0.966% | |
| 🤔 | 64 | 0.783% | |
| ⚡ | 61 | 0.746% | |
| 👀 | 41 | 0.501% |
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 891 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 8,177 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 24 August 2026 to 8 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.
Telegram’s own ‘edited’ marker: 0 of 380 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).
泰国彭世洛33岁大学保安诱骗74岁老妇进树林性侵,已落网 泰国彭世洛府警方11月7日通报,当地一名33岁男子在受害老妇住宅附近搭讪,以邀约外出用餐为借口哄骗74岁老妇坐上摩托车,却将其带至楠河沿岸偏僻树林实施性侵,事后独自骑车折返。警方调取沿线监控锁定嫌疑人,迅速抓捕。落网男子为当地一所大学在职保安,对犯罪供认不讳,辩称情绪失控无法自控。 办案人员已带其到案发树林指认取证,男子以涉嫌强奸罪移交专项调查人员。受害老妇家属强烈呼吁司法部门从严从重惩处。
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严正谴责中国公民在西港警察局内疑遭殴打致死事件 一名中国公民因涉电诈被西港警方抓捕后,疑在警察局内遭执法人员殴打致死。无论涉嫌何罪,生命权与基本人身权利都不容随意剥夺,警察局绝非法外之地。据称该局留置环境极其混乱,狭小房间关押六七十人,基本人道标准存疑。 我们严正要求柬方:立即调查死亡真相,查明是否存在警察暴力执法;封存监控录像及执法记录,严防毁灭证据;依法追究涉事人员及管理负责人责任,不得以内部调查敷衍了事;全面整改西港警察局羁押管理问题。 恳请中国驻柬大使馆高度重视,及时核实情况,提供领事协助,助家属了解真相、维护合法权益。反对电诈、支持依法打击犯罪,但打击犯罪绝不是暴力执法的挡箭牌。请媒体关注,请大使馆介入,给死者家属和公众一个明确交代!
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柬埔寨红十字会联合ICRC为宪兵开展国际人道法培训 859人参与 柬埔寨红十字会联同红十字国际委员会(ICRC)为宪兵开展国际人道法培训,共859人参与。宪兵承担治安、执法与应急处突任务,可能直接接触平民、被拘人员与伤者。 此次培训旨在让执法者掌握保护平民、限制暴力、尊重人道的原则。859人的覆盖面表明执法队伍人道法教育持续推进。
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网友曝料:前同事介绍换汇 第三次黑我3000U 十五当初酒桌上亲口说这是他兄弟,以后换汇找他。前两次正常,我离开公司后第三次直接吞了我3000U。骗子ID @uubb122,本人照片和链上记录我都留着。 十五是老板发小,这层关系别当担保。换汇只认链上记录和对方地址,前两次没事不代表第三次不黑。 我已拉黑,照片打码发群,转账哈希留好。找十五要说法,老板那边我也提一句。
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涉金运园区资金盘 网友曝遭跨国报复殴打 网友投稿称,原财通金运园区“创大集团”李女士涉太子集团背景,其伴侣非法入境大马被扣后,投稿人协助运作却遭污蔑“杀猪盘”诈骗。 随后投稿人在金边被诱至包厢及街头殴打,手机被砸,对方威胁“随时可以找到我”。投稿人掌握施暴者“郭连意”等信息,要求当事方一天内出面处理,否则将报警并持续曝光相关黑暗。
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吉隆坡酒店突袭 8人涉卖淫被捕 11月7日凌晨,吉隆坡移民局突袭一家三星级酒店,捣毁卖淫窝点,逮捕8人,包括6名外籍女子(5名印尼籍、1名泰国籍)及2名男子。 初步调查显示,涉案人员通过社交媒体招揽顾客,收费约200至230令吉,部分外籍人士涉嫌逾期逗留及滥用准证,案件正进一步调查中。
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网友曝料:缅北盘口女头目李磊 改名岩瀬穗子藏身日本 李磊,现改名岩瀬穗子,祖籍黑龙江,母亲为日本殖民满洲时期后裔,后移居日本长期住在东京。早年与男友在缅北卧虎山庄开资金盘,一个盘收割几个亿,后赴日投资滑雪旅馆,在长崎、北海道、大阪等地购置产业幕后操盘。男友一直在东南亚针对日本人搞精聊诈骗,冒充日本公检法,资金经此女和日本黑社会洗白再买房产。 被控长期涉人口贩卖、暴力管理及诈骗,经营的盘口至少10名狗推死亡,残废不计其数。盘口分布在柬埔寨波贝宝龙四合院、波哥山三期、原菩萨15公顷等地,员工每天被强制工作16至18小时。爆料人恳请中国政府介入调查其东南亚活动,彻查资金来源、洗钱及人口贩卖,并依法调查其日本居留身份,争取引渡回国。 资金盘收割几个亿,转身在日本买旅馆置产,男友在东南亚骗日本人,钱经黑社会洗白回流房产,这条链子从头到尾都算好了。盘口横跨波贝、波哥山、菩萨,16到18小时高压管理加死亡残废的数字,已经不是普通爆料能盖…
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巴基斯坦拉合尔捣毁两处非法呼叫中心 12人被捕 11月6日,巴基斯坦国家网络犯罪调查局拉合尔分局突袭Batapur地区“Solution Hub”及Punjab Housing Society“Task Taker”两处非法呼叫中心,逮捕12人(10男2女)。 涉案团伙冒充Rogers、Bell、Telus、AT&T等美加电信客服,以手机升级、套餐优惠等名义骗取海外民众个人及金融信息,进而实施盗刷。警方查获笔记本电脑、台式机及手机共28件,已送数字取证,案件正在调查中。
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沙巴斗湖理疗中心突袭 中国籍女子招揽卖淫判监5个月 马来西亚沙巴州斗湖警方11月4日晚接线索后,安排便衣乔装顾客进入理疗中心,31岁中国籍女子以700令吉提供性服务,交易达成当场被捕,查获现金、使用过的避孕套及手机。法院批准延扣3天,女子在斗湖推事庭认罪,依刑事法典第372B条文判监5个月、罚款4000令吉,缴不清加监2个月。 斗湖这次是便衣钓鱼加当场取证,证据链从现金到物证一条龙,认罪判罚没有拉扯空间。马来西亚近期对理疗中心这类挂羊头卖狗肉的场所查得紧,外籍身份加违法交易,判完还有移民程序等着。
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Showing the 12 most recent of 1,222 posts we hold for @DNY88880. 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.
We recorded 14 posts on @DNY88880 as deleted — posts this register held that were missing from the channel’s public page on two separate reads, taken from different network addresses at least an hour apart.
A deletion is not wrongdoing. This register can see that a post it held is no longer on the channel’s public page, and when — not why. Expired ad placements, reposts, rotating links and corrections all look the same. This is a count of recorded detections, not an exact total: it misses deletions we could not see, because only a post we held and later re-read inside the page can be seen to go, and it may include a small number of wrong records. How this is measured.
Names
Channels on the register whose handles appear in this channel's posts.
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.
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.
Read from Telegram’s recommendation API, most recently 19 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.
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.
This channel appears in 21 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
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 7 November 2026 — this entry's latest reading, not the date you are reading this.
“🥇东南亚华人大事件” (@DNY88880), 100,312 subscribers as measured 7 November 2026. Telegram Register, tgregister.com/channel/DNY88880.
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.