Channel
@baoguang_00
On this record: Topic · Observations · Also posting the same content · Growth · Engagement · What this channel posts · Posts · Citations · Cite this entry
663subscribers
+0 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1002511601565 |
|---|---|
| Type | Channel |
| Username | @baoguang_00 |
| Description | 🌏 飞机导航 @xinwen006 🔍新闻热搜： 曝光群1： @baoguangqun06 曝光群2： @baoguang_00 曝光群3： @baoguang_pd 🔍吃瓜群总： 吃瓜群1： @Chiguatoutiao3 🔍探讨群聊： @baoguangqun006 ✍🏻关键词搜索： #网红查黑问题 #+名字 #曝光 #悬赏 #骗子 #名字 ☎️曝光/商务：@iu9886 #柬埔寨 #菲律宾 #缅甸 # |
| Created | Between 1 March 2025 and 31 July 2025— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 8 August 2026 |
| Last confirmed live | 8 August 2026 |
| Measurements held | 2 |
| On Telegram | t.me/baoguang_00 |
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 11 August 2026 and assigned it the closest of 31 fixed categories, at 82% 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.
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.
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.
| Posted first | Then | Overlap | Gap |
|---|---|---|---|
| @baoguangqun06/355536 Jun 2026, 09:54 UTC | @baoguang_00/32491 · this entry6 Jun 2026, 09:54 UTC | 1.00 | under a minute |
| @baoguangqun06/355546 Jun 2026, 09:54 UTC | @baoguang_00/32492 · this entry6 Jun 2026, 09:54 UTC | 1.00 | under a minute |
| @baoguang_00/32496 · this entry6 Jun 2026, 09:54 UTC | @baoguangqun06/355586 Jun 2026, 09:54 UTC | 1.00 | under a minute |
| @baoguang_00/32497 · this entry6 Jun 2026, 09:54 UTC | @baoguangqun06/355596 Jun 2026, 09:54 UTC | 1.00 | under a minute |
| @baoguang_00/32499 · this entry6 Jun 2026, 09:54 UTC | @baoguangqun06/355616 Jun 2026, 09:54 UTC | 1.00 | under a minute |
| @baoguang_00/32500 · this entry6 Jun 2026, 09:54 UTC | @baoguangqun06/355626 Jun 2026, 09:54 UTC | 1.00 | under a minute |
| Channel | Matching posts | Text overlap | Typical gap | Published first |
|---|---|---|---|---|
| @baoguangqun06 | 11 (8/8 hand-verifiable sample passed) | 1.00 | under a minute | this entry (10–1) |
| @baoguang_pd | 10 (8/8 hand-verifiable sample passed) | 1.00 | under a minute | even |
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. None of the 6 matches recorded here fall after that date, so for this entry we cannot say whether any of them carried a credit. The duplication is measured; the absence of attribution is not.
“Published first” means first in this corpus. We hold 11 comparable posts for this entry, running 6 June 2026 to 7 June 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.
Across the whole group of 3, the earliest publisher we hold is @baoguang_pd. That is a statement about our reading window, not a claim of authorship.
Recorded under the keys clone_mutual · clone_source, 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.
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.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 8 Aug 2026, 02:34 | 663 | no change |
| 7 Aug 2026, 18:44 | 663 | first reading |
13 posts held, back to 6 June 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 1 pageof Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 13 posts for this entry, the most recent from 7 June 2026. An engagement rate over an empty window would be a number about nothing.
Lifetime counters from Telegram’s own channel header, read 8 August 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 6 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.
479名涉嫌网络诈骗的中国公民被柬埔寨王国遣返 2026年6月5日至6日，根据副首相兼内政部长阁下、内政部长阁下及内政部领导的高层建议，移民局局长索维斯纳中将指示调查执法局与中国驻柬埔寨大使馆合作，将479名涉嫌网络诈骗、非法居留和工作的中国公民（其中16名为女性）遣返出境。其中，306名中国公民（其中7名为女性）在暹粒吴哥国际机场门岗警察局乘坐专机被遣返，另有173名中国公民（其中9名为女性）在德乔国际机场门岗警察局乘坐专机被遣返。 驱逐上述外国人符合柬埔寨王国首相洪玛奈阁下为清除和消除柬埔寨王国境内发生的一切网络犯罪而采取的严格法律措施，以及副首相兼内政部长萨尔索卡博士阁下的强力指导，旨在确保本地区乃至全世界公民的安全，特别是打击网络犯罪的幕后主使，并解救被诱骗参与网络犯罪的受害者，使他们能够自由返回各自的国家。 ✅投稿联系 @iu9886
金边200万美元绑架、勒索、杀人抛尸案告破 5月29日晚，金边朗哥区巴库村一处空地的一辆白色普锐斯轿车内，发现一具被抛尸的中国籍男子尸体，引发广泛关注。 案发后，柬埔寨警方展开案件侦破工作，目前成功抓获4名中国籍犯罪嫌疑人。据披露，此案系中国籍同胞内部恩怨引发。死者与嫌疑人在中国国内便存有仇怨，嫌疑人一路尾随死者至柬埔寨实施报复杀人并抛尸。 目前，4名嫌犯正接受审讯，警方正全力追捕其余在逃同伙。 ✅投稿联系 @iu9886
西港皇乐山庄黑公司内幕架构曝光 庆总、老孙、黄冲、浩南、星期五、王子涛，大峰等人。 你们习惯了站在高处指点别人，却很少低头看看自己走过的路。有人把算计当本事，把压榨当管理，把欺负老实人当成能力，把纸醉金迷当成成功。 老孙，你应该最清楚，有些钱来得快，去得更快，有些路看似捷径，走到最后却是绝路。人在顺风顺水的时候，总以为自己聪明过人，可真正决定一个人命运的，从来不是小聪明，而是底线。 黄冲、浩南、星期五，你们整日流连包厢吸毒，把脑子都吸坏了，所有的情绪指向公司内部员工.已上照片是王子涛，后续我会一一附上你们所有人的照片，包括你们家人我都会一一附上！ 王子涛，大峰，你身为主管，本该为员工遮风挡雨，却把员工当成发泄情绪的工具。心情好了高高在上，心情不好便拿员工出气。自己享乐无度，却让基层员工为你的挥霍埋单。你以为压得住别人就是本事，其实真正有能力的人，从来不需要靠践踏别人来证明自己。 古人云：德不配位，必有灾殃；人不配财，…
金边警方捣毁中国籍绑架勒索团伙 其中一人已被拉黑名单竟然又潜回了柬埔寨！ 6月4日，金边市警方成功捣毁一个企图实施绑架勒索的有组织犯罪团伙。 行动中，警方共抓获4名中国籍男子，并现场缴获1支ZORAKI 906 TD手枪、6发子弹和3副手铐。 金边市警察局长尊那林透露，落网嫌犯中包含一名上了入境黑名单的危险分子。首嫌翁某（WENG SHENG FENG，43岁）曾因非法拘禁、酷刑虐待及非法持枪勒索，于2023年11月在柬坐牢15个月，刑满后被驱逐出境并禁止入境。然而，今年5月初，他花费1200美元经老挝偷渡回流至柬埔寨上丁省，随后潜入金边纠集同伙。其余3名落网同伙分别为廖某、宋某和沈某。 尊那林强调，该团伙当时正在密谋策划一起绑架案，若非警方及时收网，后果不堪设想。 目前，4名嫌疑人已被移交轻刑司法办案处，正接受进一步法律审理。 ✅投稿联系 @iu9886
#泰国资讯：北碧府截获81部iPhone！4名中国人偷渡入境，疑欲前往缅甸诈骗园区 泰国北碧府警方近日在例行巡逻期间成功拦截一辆可疑皮卡车，当场查获4名中国籍男子及1名泰国籍司机，并搜出大量手机设备。经清点，车内共发现77部全新iPhone，加上4名中国籍人员随身携带的手机，总数达到81部。 警方调查显示，4名中国籍男子涉嫌通过柬埔寨边境非法进入泰国境内，随后计划前往泰缅边境三佛塔镇（Three Pagodas Pass）附近地区，并准备进入缅甸境内某涉嫌从事网络诈骗活动的园区工作。执法人员怀疑，查获的大批iPhone设备与相关诈骗团伙运营活动有关。 被捕的泰国籍司机向警方供称，其受人委托负责接送上述人员，并收取了2000泰铢作为运输报酬。目前警方正在进一步核查涉案人员身份及资金往来情况，以厘清背后组织网络。 ✅投稿联系 @iu9886
大马又打掉两个窝点，29名中国男女被控上庭 6月5日，马来西亚霹雳州怡保警方把29名中国籍男女押上法庭。 这批人主要涉及没有合法证件、逾期逗留等问题。其中17人还牵涉诈骗和网赌宣传案件。 所有被告当庭都不认罪。这次案件分成两部分。 第一部分是13名中国籍被告，包括11男2女。他们被指在怡保巴占一处住宅内，合谋做线上债务诈骗。 简单来说，就是用不存在的线上借贷、债务服务来骗人。 如果罪名成立，最高可被判监禁5年、罚款，或两者兼施。 由于部分被告还涉及非法逗留，法庭没有批准保释。案件将在6月24日再过堂。 第二部分是4名中国籍被告。他们被指在同一住宅区的另一间民宅内，合谋在网上宣传带有赌博或投注内容的平台。 如果罪名成立，可被罚款5000至5万令吉，并可被判监禁不超过3年。 法庭允许这4人各以4000令吉保释，但条件是必须有2名住在霹雳州的马来西亚公民担保。 同时，他们还要交出护照，并在每个月1日和15日到附近…
#最新消息：波贝今天早上一栋大楼被宪兵突袭了，怀疑该建筑内住有外籍人员，涉嫌秘密从事网络诈骗活动。 截止目前为止，局势已被宪兵控制并查获了一个网络诈骗团伙，共抓获21名嫌疑人 ✅投稿联系 @iu9886
#最新消息：波贝奥克罗夫乡萨马基棉吉村一栋大楼被突袭，抓铺约21名狗推，目前已经开始装车了。 ✅投稿联系 @iu9886
马莱县惊现可疑物资运输车！疑涉网络诈骗活动 6月6日，边境地区媒体在卜迭棉芷省马莱县斗蓬乡进行实地采访调查时，发现一辆大型货运卡车正在运输大批物资，据现场观察，该批物资数量较大，运输方式较为特殊。根据媒体掌握的信息，相关物资疑似与网络诈骗（Online Scam）活动所使用的设备及后勤保障用品有关。 PS：谁家公司搬家撞枪口上了🤣🤣🤣 ✅投稿联系 @iu9886
刘会长同款衣服 Casablanca经典真丝长袖衬衫，价格在950刀。这种，是不是人得起飞咯～～ 你即使知道他杀人放火，但慑于或碍于各种因素，都是闭口。 他在前面杀人放火，转头就做慈善，捐资助学，还回报桑梓，各种官方报道，各路官人抬轿，他成了家乡人的骄傲，成了官人宴席上的座上宾... ... 但一旦塌房，马上切割，就不认识了。就这么现实且残酷。 所以，我们其实都一样，人就是现实的动物。也是欺软怕硬的动物。 ✅投稿联系 @iu9886
柬埔寨清扫园区以后，现在二手市场价格崩了 从家具、冰箱、彩电、大沙发，到电脑、平板、手机， 还有二手汽车，豪车价格全面下跌 那些园区撤离时甩卖时接手的二手老板，收的时候笑嘻嘻，心里直喊便宜，这些人真傻帽。 现在倒好，全部变成库存，流动不了，价格也全面下跌， 真是愁呀，也不知道什么时候能好转， 也不知道人什么时候来，卖吧要割肉，还不一定能卖掉。 ✅投稿联系 @iu9886
#泰国资讯：春武里邦盛公寓藏大型网赌运营中心 资金流水逾5000万泰铢 6月5日，泰国网络犯罪调查警察第二警区（Cyber Police Region 2）联合相关执法单位展开突击行动，成功捣毁位于春武里府邦盛地区一处大型网络赌博运营窝点，初步调查显示，该团伙资金流水超过5000万泰铢。 据了解，此次行动是根据第二警区调查指挥官打击网络犯罪政策部署，由技术犯罪调查与打击部门联合“第二警区网络犯罪中心”共同执行搜查及抓捕任务。警方经过前期调查掌握确凿证据后，对目标公寓展开突袭。 行动期间，警方封锁现场并进入涉案房间时，部分嫌疑人企图销毁犯罪证据，将电脑、手机以及电子存储设备从公寓8楼抛下，导致楼下停放车辆及其他公共财产受损。不过，警方迅速控制现场，成功保全大量关键证据。 搜查过程中，执法人员查获多台台式电脑、笔记本电脑、手机以及大量用于运营网络赌博网站的电子设备，并提取相关数据作为后续调查证据。 经初步调查发现，该团伙涉…
Showing the 12 most recent of 13 posts we hold for @baoguang_00. 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.
Citation-graph rank — 1,413,546 of 1,480,688entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.
Named by 1 registered channel — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.
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.
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 8 August 2026 — this entry's latest reading, not the date you are reading this.
“东南亚热点新闻” (@baoguang_00), 663 subscribers as measured 8 August 2026. Telegram Register, tgregister.com/channel/baoguang_00.
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.