#频道互推 #相似推荐 ------------------------------ 📢 中国大事件/中文日记 📢 东南亚大事件|华人新闻|热点爆料 📢 东南亚大事件 「新闻曝光」 📢 全球新闻事件 📢 西安艺妓 📢 缅北大事件曝光 📢 Telegram-环球新闻时讯 📢 事件曝光 新闻爆料 📢 柬埔寨新闻投稿 📢 今日热点 ------------------------------ ☁️ 互推入口:@sooo

Channel
安危事件
@anweishijian80
On this record: Growth · Engagement · What this channel posts · Posts · Citations · Cite this entry
18,549subscribers
+4,804 since we began measuring on 9 August 2026
Risers and fallers across the register · movement among entries of 10,000–31,623.
Register entry
| Telegram ID | -1001647196440 |
|---|---|
| Type | Channel |
| Username | @anweishijian80 |
| Description | 投稿,爆料 商务合作 👉 @qs444 双向机器人👉 @TGBGJQ88_bot 防失联导航: @TGBG8888888 Hello @Telegram My channel has not violated the rules and policy of using Telegram. #头条 #曝光 #吃瓜 #缅北 #博彩 #新闻发布 #行业新闻 #博彩热点 #曝光骗子 |
| Created | Between 1 December 2021 and 30 April 2023— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 9 August 2026 |
| Last confirmed live | 16 August 2026 |
| Measurements held | 8 |
| Confirmed unchanged | 1 time, most recently 16 August 2026 |
| On Telegram | t.me/anweishijian80 |
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 16 Aug 2026, 17:38 | 18,549 | -131 |
| 15 Aug 2026, 04:24 | 18,680 | -24 |
| 13 Aug 2026, 23:26 | 18,704 | -45 |
| 12 Aug 2026, 16:43 | 18,749 | +5,049 |
| 11 Aug 2026, 15:22 | 13,700 | -20 |
| 10 Aug 2026, 14:31 | 13,720 | -25 |
| 9 Aug 2026, 15:14 | 13,745 | no change |
| 9 Aug 2026, 13:32 | 13,745 | first reading |
Engagement
94 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 19 pagesof Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 17.9%
- avg views ÷ 18,549 subscribers
- Avg views / post
- 3,310
- 88 posts measured
- Reaction rate
- —
- this channel exposes no reaction counts
- Posts in window
- 94
- of 94 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.
| Window | Rolling 30 days · latest post in window 16 August 2026 |
|---|---|
| Posts held | 94 (7 August 2026 – 16 August 2026) |
| Views total | 291,695 |
| Reactions total | — |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 16 Aug 2026, 21:48 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
- ≈12,500
- Videos
- ≈1,610
- Links
- ≈5,190
Lifetime counters from Telegram’s own channel header, read 16 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.
- Video runtime
- 9m 00s
- Average length
- 1m 17s
Measured directly from 7 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.
Recent posts
在 Telegram 里找内容,先打开 SOSO 搜搜。 频道、群组、帖子、贴纸都可以搜;也可以从发现页继续浏览。
安危事件 pinned a photo
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#菲律宾资讯 马尼拉河道惊现行李箱藏女尸!警方靠纹身寻找死者身份⚠️ 菲律宾塔吉格市近日发生一起命案。一只可疑行李箱漂浮在河道内,被发现后警方立即展开调查,打开行李箱后发现里面藏有一具女性遗体。 警方初步判断,死者年龄约在35至40岁之间,目前身份尚未确认。调查人员已对现场进行勘查,并通过失踪人口资料展开身份核查。 警方透露,死者身上有两处较为明显的纹身,可能成为确认其身份的重要线索。其中,腿部纹有黑色环带,并结合几何及部落风格图案;手臂上则有菲律宾太阳图案纹身。 目前,警方正进一步调查行李箱被遗弃的具体时间、地点,以及案件是否涉及其他人员。同时,警方呼吁公众,如认识符合上述纹身特征的女性,或掌握近期人员失踪相关信息,应及时向警方提供线索。 案件仍在进一步调查中,警方希望尽快确认死者身份,并进一步查明事件经过及背后真相。
#菲律宾资讯 #酒店咖啡厅发生盗窃!巴勒斯坦男子偷走现金,当场被捕⚠️ 菲律宾奎松市一家酒店咖啡厅近日发生盗窃事件。一名36岁的巴勒斯坦籍男子涉嫌趁工作人员不注意,拿走装有现金的钱袋和现金盒,随后被酒店安保人员根据监控录像当场拦截。 警方表示,事件发生于7月23日晚约11时06分,地点位于奎松市蒂莫格大道一家酒店咖啡厅。调查显示,男子进入咖啡厅后,疑似趁收银员疏忽,将一个现金袋和一个空现金盒拿走,并准备离开。 不过,酒店监控完整记录了相关过程。工作人员发现异常后立即通知安保人员,并在出口处将男子拦下。警方赶到现场后,从其身上查获被盗物品及约5020比索现金。 警方透露,该男子此前还涉及其他案件,包括涉嫌诈骗、拒绝配合执法以及盗窃等。 目前,嫌疑人已被移交检察机关,警方将以盗窃罪对其提出指控,同时继续调查其是否还涉及其他案件。
#网友吐槽 想过出门好好喂狗,但没想过狗吃相这么难看。 号称波贝最豪华的水会——文南•阁(原波贝壹号•水韵会所),我就说,既然是这么高端的场所,怎么里面还会有小偷小摸?是你老板开不起工资,还是说你老板专门培训过你们,让你们干这种掏客人钱包、偷鸡摸狗的事情? 我看不用叫什么“文南•阁”了,再改个名,就叫“扒手阁”吧。看你们这些人,根本不像正儿八经干会所的。真是信了你们的鬼话,说什么“只有客人手牌才能开柜”。 干你娘的,一群专业扒手! 出现这种事情,就能看出来内部管理到底有多松散、多不靠谱。你倒是查啊?一直推三阻四的。后台开柜记录看不到,那你们查了吗?最后跟我说报警处理,然后结果呢?钱丢了,就这样不了了之。 我是真庆幸,现在兄弟姐妹们走得差不多了。不然进了你这个“扒手阁”,指不定还要脱一层皮。 也奉劝还在波贝的兄弟姐妹们,一定要避坑,千万千万不要去“文南•阁”送钱。有多少东西,能给你偷多少,最后你还得给扒手买单。 而…
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#菲律宾新闻 达沃暴雨引发洪灾!居民爬屋顶避险,老杜家族紧急援助 菲律宾达沃市遭遇强降雨袭击,多地爆发严重洪水。部分社区积水迅速上涨,居民家中被淹,一些家庭被迫爬上屋顶等待救援。 受灾较严重的塔洛莫(Talomo)地区,多名居民因洪水突然涌入家中一度受困。随着水位持续上升,部分民众只能暂时转移至屋顶避险,等待救援人员救助。 灾情发生后,救援行动迅速展开。保罗·杜特尔特以及副市长罗德里戈·杜特尔特二世办公室启动援助,为受灾居民提供食品和生活物资,并协助转移受困群众。 目前,部分区域积水已经开始消退,居民陆续返回家中清理淤泥并统计损失。当地政府提醒民众,雨季期间仍需关注天气预警,避免进入危险区域。 此次洪灾再次凸显菲律宾雨季期间极端天气带来的风险,相关部门正持续开展灾害监测和后续救援工作。
#国内资讯 60余人落网!山东烟台莱州市公安成功打掉一个网络直播诈骗团伙! 莱州市公安局7月23日对外披露案件详情:近日,莱州市公安局结合烟台市“齐鲁守护·夏季攻势”专项行动,开展跨省集群收网,奔赴江苏常州成功打掉一个依托直播间售卖玉石、以高价回收、抽奖模式引流实施诈骗的犯罪团伙,一举抓获嫌疑人60余名,现场查获玉石、首饰、小家电等涉案物品一批。 5月11日,莱州市公安局刑侦大队获取警情,文峰路街道杨女士在微信直播间购买物品时被骗人民币3万余元。接警后,民警围绕网络流、资金流顺线追踪研判,并对接烟台市公安局开展技术支撑,锁定位于江苏省常州市武进区创业园内、以冯某、李某为首的直播诈骗团伙。 经实地侦查核实,该团伙通过售卖玉石、承诺高价回收、举办抽奖活动吸引客户充值,诱导受害人转账后失联,警方初步锁定涉案人员40余名。 7月13日,抓捕时机成熟,莱州公安抽调40余名精干警力组成专案组奔赴常州开展跨省收网。行动期间恰逢台风过…
#国内资讯 重庆从柬埔寨和老挝押解1800名涉诈人员‼️‼️ 据重庆市政府新闻办7月24日2026年全市反诈工作新闻发布会,今年以来,重庆全市电诈警情数、立案数、损失数同比分别下降38%、36.4%、43%,破案数、涉案人员打击处理数同比分别上升124.2%、43.9%,累计为群众守住超8亿元潜在被骗资金。 今年以来,重庆警方统筹境内境外“两个战场”,成功打掉境内外电诈犯罪团伙198个,特别是彻底摧毁长期盘踞缅甸北部、严重危害我国公民生命财产安全的“徐老发”特大武装电诈犯罪集团;先后从柬埔寨、老挝押解1800余名涉诈人员回渝,其中97.7%被依法逮捕,境外诈骗团伙的生存空间被进一步挤压。
Showing the 12 most recent of 94 posts we hold for @anweishijian80. 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
Citation-graph rank — 1,402,376 of 1,481,502entries 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.
Mentions
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.
Named by
Channels on the register whose posts name this channel's handle.
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.
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 16 August 2026 — this entry's latest reading, not the date you are reading this.
“安危事件” (@anweishijian80), 18,549 subscribers as measured 16 August 2026. Telegram Register, tgregister.com/channel/anweishijian80.
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.