Channel
@bbsooo
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Telegram's recommendations · Cite this entry
57,303subscribers
-52,324 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 31,623–100,000.
| Telegram ID | -1001500679252 |
|---|---|
| Type | Channel |
| Username | @bbsooo |
| Description | #东南亚 #柬埔寨 #菲律宾 #缅甸 #泰国 #迪拜 热门曝光、新闻频道，安危事件，曝光爆料 东南亚必备的曝光频道 商务合作： @zxx16 投稿机器人 @bbsoobot |
| Created | Between 1 December 2020 and 30 April 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 13 October 2026 |
| Measurements held | 38 |
| Confirmed unchanged | 1 time, most recently 13 October 2026 |
| On Telegram | t.me/bbsooo |
Gambling & betting — 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 100% 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.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 13 Oct 2026, 21:10 | 57,303 | -1,533 |
| 10 Oct 2026, 13:41 | 58,836 | -1,359 |
| 6 Oct 2026, 11:17 | 60,195 | -4,886 |
| 1 Oct 2026, 07:02 | 65,081 | -25,593 |
| 18 Sept 2026, 11:39 | 90,674 | -3,088 |
| 16 Sept 2026, 06:58 | 93,762 | -3,746 |
| 14 Sept 2026, 14:59 | 97,508 | -3,170 |
| 13 Sept 2026, 01:41 | 100,678 | -5,690 |
| 11 Sept 2026, 03:56 | 106,368 | +4,272 |
| 8 Sept 2026, 07:02 | 102,096 | -4,516 |
| 5 Sept 2026, 02:20 | 106,612 | -2,536 |
| 3 Sept 2026, 09:27 | 109,148 | -7,569 |
| 2 Sept 2026, 01:43 | 116,717 | +12,928 |
| 1 Sept 2026, 00:25 | 103,789 | -8,109 |
| 30 Aug 2026, 21:28 | 111,898 | -2,615 |
| 29 Aug 2026, 19:56 | 114,513 | +12,837 |
| 28 Aug 2026, 17:57 | 101,676 | -11,999 |
| 27 Aug 2026, 20:57 | 113,675 | +10,306 |
| 26 Aug 2026, 19:12 | 103,369 | -7,108 |
| 25 Aug 2026, 19:29 | 110,477 | first reading |
1,033 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 140 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 62 of 501 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 14 October 2026 |
|---|---|
| Posts held | 1,033 (7 August 2026 – 14 October 2026) |
| Views total | 1,278,140 |
| Reactions total | 66 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 14 Oct 2026, 14:32 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 14 October 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 37 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.
143 reactions across 138 posts, in 14 distinct kinds. The most used accounts for 14.7% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 🎉 | 21 | 14.7% | |
| ❤ | 19 | 13.3% | |
| ⚡ | 18 | 12.6% | |
| 👏 | 15 | 10.5% | |
| 😁 | 15 | 10.5% | |
| 🤩 | 15 | 10.5% | |
| 👍 | 14 | 9.79% | |
| 🔥 | 12 | 8.39% | |
| 🥰 | 8 | 5.59% | |
| 💯 | 2 | 1.40% | |
| 👀 | 1 | 0.699% | |
| 👌 | 1 | 0.699% | |
| 😎 | 1 | 0.699% | |
| 😴 | 1 | 0.699% |
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 142 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 143 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 9 August 2026 to 14 October 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.
#缅甸新闻：美元汇率飙升 至1美元兑4600缅元 据UMFCCI消息，敏昂莱集团拟向央行追加借款2100亿缅元，并传出将印5万面额新钞，引发市场恐慌。 仰光美元汇率升至1美元兑4600缅元，黄金、美元抢购潮再现。燃油连涨三周，每升破5000缅元，加油站限购断货。 棕榈油每缅斤涨至23000至30000缅元。金价每缅两突破10万缅元，部分金商暂停交易。 经济人士指出，军政府靠印钞弥补赤字，通胀持续恶化。
#越南新闻：越南拟修法推进酒吧酒店等场所全面禁烟及严控售烟 据越南媒体昨天报道，《越南烟草危害防控法》修订草案目前正接受审查，预计年底提交国会审议。 草案提出，酒吧、卡拉OK、舞厅、酒店及客运站等原本允许设独立吸烟区的室内场所，以及轮船和火车等交通工具，将分阶段逐步过渡至全面禁烟。此外，草案还拟禁止销售点展示卷烟产品，严禁电商与自动售货机售烟，并禁止在学校及医院外100米范围内设售烟点。电子烟、水烟及尼古丁袋等亦被列入全链条禁止范围。该新规预计于2027年7月1日起生效。
#新加坡新闻 新加坡政府联手谷歌开发AI反诈工具 可识别聊天软件中的诈骗话术 10月14日，新加坡数码发展及新闻部长杨莉明宣布，政府科技局正与谷歌旗下人工智能研究机构DeepMin d合作，开发一款手机AI反诈工具，能够实时分析聊天内容，识别潜在诈骗话术并向用户发出警告。 这项技术可识别冒充政府机构、银行及熟人等诈骗手法，还能分析骗子在聊天过程中诱导转账、索取个人资料等行为，让用户在被骗之前收到提醒。 与传统反诈系统不同，新工具直接在手机上运行AI模型，聊天内容无需上传至外部服务器，在识别诈骗的同时保护用户隐私。 该技术主要针对安卓手机，未来可用于聊天软件的诈骗检测。目前具体安装方式及正式开放时间尚未公布。
缅甸佤邦抓获3名中国籍在逃人员，已通过边境口岸移交中方！ 10月14日，佤邦联合军（UWSA）发布通报称，应中国方面协查请求，佤邦有关人员近日成功抓获3名被中方通缉的中国籍在逃人员，并通过中缅边境勐阿口岸移交中国有关部门。 据通报，此次移交同时移送了涉案证据材料及人员身份信息。不过，官方尚未披露3人的具体涉案罪名及案件详情。 此外，佤邦方面曾于10月5日通过边境口岸向中国移交32名非法入境的中国籍人员。
美国和柬埔寨将联合打击跨国非法金融与网络诈骗 美国驻柬使馆今天披露：美国驻柬埔寨临时代办吉特尔与美国财政部副助理部长罗伯特·卡普罗斯拜会了柬埔寨国家银行（NBC）行长谢丝蕾，双方就加强金融领域治理及推进柬埔寨金融发展展开深入讨论。 美方强调，将继续致力于与柬方合作打击针对美国公民的网络诈骗等非法金融活动，共同构建安全、透明且具备韧性的金融环境。
柬埔寨内政部：已经抓了77名警察 柬埔寨内政部部长发言人任拉塔纳对媒体表示，政府开展强力打击网络诈骗行动以来，已有77名涉案的国家警察被逮捕并判刑入狱。 任拉塔纳表示，柬埔寨政府迄今为止一直在以极为严厉的手腕清除网络诈骗犯罪。多个主要头目已被抓获，部分在柬埔寨服刑，部分已被遣返回原籍国。 任拉塔纳说，“大型窝点已被关闭，约40万名涉案外国人员已被驱逐出境以及自愿离境。” 不过，发言人也承认，网络诈骗犯罪仍在继续发生，表现形式为零星分散形式，也有人企图再次进行大规模运作。但执法部门绝不姑息，一旦接到情报，必须彻底清除并断绝所有犯罪链条。
😁1
#非洲新闻：美司法部跨国打击行动重创西非诈骗网络 上周，在一场多国联合开展的“联合打击周”行动中，基地位于西非的跨国网络诈骗集团遭到重创。 本次行动取得了显著成效：共抓获数十名犯罪嫌疑人，成功解救100多名人口贩卖受害者，并彻底封禁与该地区诈骗中心关联的370多万个虚假社交媒体账号，创下历史最大规模封号纪录。 美国司法部对此表示，此次大规模封号与逮捕行动仅是专项打击的开端。
❤1
#泰国新闻：警方破获特大网络诈骗案 缴获逾5亿泰铢资产 昨天，泰国网络犯罪打击中心（ACSC）联合中央调查局（CIB），在曼谷及清迈、春武里等10府展开联合行动，捣毁一个特大网络诈骗团伙，共抓获39名嫌犯（含30名泰籍、8名中籍及1名缅甸籍）。 该团伙通过在Facebook冒充“专家”推广虚假股票投资吸引受害人，诱导其下载假APP并转账至13个公司账户。行动中，警方查扣了包括8栋豪宅、豪车、数字货币（USDT）在内价值超5亿泰铢的资产。该团伙涉及至少75起案件，涉案金额达1.73亿泰铢。
❤1
🇱🇦老挝加强出租场所监管：包庇电诈人员或被吊销营业执照 10月14日，老挝公安部发布通知，要求全国房东、企业及经济特区加强对出租场所的管理，防止网络诈骗、网络赌博团伙利用租赁物业从事违法活动。** 通知要求，业主如发现可疑行为，应及时向警方报告。对于故意包庇、窝藏涉案人员，或拒不配合调查的责任方，相关部门将视情况予以警告、罚款；经两次警告仍未改正的，可能被责令停业，或被吊销营业执照。 老挝公安部公布的数据显示，2026年前9个月，全国共开展153次打击行动，抓获涉及31个国籍的相关嫌疑人10,651名。
#菲律宾新闻 近180名中国教师离菲引关注：中国驻菲大使发声，呼吁维护华文教育与中菲文化交流 近180名中国教师离菲 中国驻菲律宾大使井泉10月13日公开发声，批评近期针对华文教育和华文教师的攻击，并呼吁菲律宾各大学、孔子学院、华文学校及菲华社团不要受到恐吓，继续推动中菲教育与文化交流。 井泉在亚典耀大学孔子学院成立20周年活动上表示，将华文教育抹黑为中国的“统战工具”毫无根据。 中国驻菲使馆也发表声明，谴责针对华语教师的行为，呼吁各方维护教育与文化交流，避免中菲民间关系进一步疏远。
#网友反馈：这部大皮卡就是联合国毒品和犯罪问题办公室（UNODC）办事处的车辆。 该机构常驻柬埔寨，办事点设在金边，主要协助当地打击电信诈骗、人口贩运、毒品等跨国犯罪，本次派员到场观摩这场执法行动。 不过他们在柬埔寨没有执法权，不能抓人、查封场所，只负责提供技术支持、调研见证以及相关业务培训。
#马来西亚新闻：马来西亚将加强与中国合作，联手打击网络诈骗、追查被盗资金 正在北京进行为期5天工作访问的马来西亚副首相阿末扎希表示，马来西亚希望进一步加强与中国的合作，重点打击网络诈骗、开展跨境调查，并追回诈骗及其他非法活动涉及的被盗资产。 阿末扎希指出，网络诈骗涉及多个国家，单靠一国执法难以解决，因此马中双方将加强情报共享，协调调查和执法行动。 他透露，马来西亚已于9月10日参与打击电信与网络诈骗国际联盟的联合计划，并将跨境调查和追回被盗资产列为优先事项。 此外，马中两国也已成立联合安全委员会，加强打击毒品走私的合作，包括共享情报、调查贩毒活动及毒品加工设施。 阿末扎希还表示，他已于今年7月向马来西亚国会下议院提呈《网络罪案法案》，希望进一步完善打击网络犯罪的法律框架。
Showing the 12 most recent of 1,033 posts we hold for @bbsooo. 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.
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 14 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 8 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 13 October 2026 — this entry's latest reading, not the date you are reading this.
“东南亚大爆料（曝光）” (@bbsooo), 57,303 subscribers as measured 13 October 2026. Telegram Register, tgregister.com/channel/bbsooo.
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.