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Channel

全网曝光

@baoguangdashijian

2 usernames

On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Posts edited after publishing · Citations · Cite this entry

57,628subscribers

+17,503 since we began measuring on 21 August 2026

Risers and fallers across the register · movement among entries of 31,623–100,000.

Register entry

Telegram ID-1001722551214
TypeChannel
Usernames@baoguangdashijian @quanwangbaoguang
CreatedBetween 1 December 2021 and 30 April 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded21 August 2026
Last confirmed live25 October 2026
Measurements held70
Confirmed unchanged1 time, most recently 25 October 2026
On Telegramt.me/baoguangdashijian

Topic

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 57% 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.

Growth

32,99562,99047,992.557,62821 August 202625 October 2026
70 measurements spanning 65 days, net +17,503. 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 28,496–67,489 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 70
Measured (UTC)SubscribersChange
25 Oct 2026, 09:1057,628+2,676
25 Oct 2026, 01:3954,952+1,333
24 Oct 2026, 09:5553,619+3,518
24 Oct 2026, 02:2050,101+5,243
23 Oct 2026, 10:3044,858-399
23 Oct 2026, 05:2545,257-503
22 Oct 2026, 10:2945,760-341
22 Oct 2026, 03:3046,101-1,098
21 Oct 2026, 01:5747,199-223
20 Oct 2026, 23:0647,422-667
20 Oct 2026, 01:2748,089-605
19 Oct 2026, 18:5748,694-205
18 Oct 2026, 22:0648,899-357
18 Oct 2026, 16:4649,256-733
18 Oct 2026, 00:5949,989no change
17 Oct 2026, 19:0149,989-309
17 Oct 2026, 03:4750,298-401
16 Oct 2026, 17:4150,699-885
16 Oct 2026, 03:5051,584-128
15 Oct 2026, 14:0851,712first reading

Engagement

1,244 posts held, back to 20 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 131 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
0.956%
avg views ÷ 57,628 subscribers
Avg views / post
551
564 posts measured
Reaction rate
0.249%
reactions ÷ views · ER floor
Posts in window
703
of 1,244 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 48 of 564 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 24 October 2026
Posts held1,244 (20 August 2026 – 24 October 2026)
Views total310,698
Reactions total49
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken25 Oct 2026, 01:00 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

Video runtime
3h 06m
Average length
36s

Measured directly from 313 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

72 reactions across 71 posts, in 9 distinct kinds. The most used accounts for 16.7% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤1216.7%
🔥1216.7%
⚡912.5%
🎉79.72%
👏79.72%
🤩79.72%
👍68.33%
😁68.33%
🥰68.33%

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 72 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 72 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 5 September 2026 to 24 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.

Recent posts

24 Oct 2026, 19:55 UTC5 viewsread 25 October 2026

#频道互推 #相似推荐 ------------------------------ 📢 缅北老街吃瓜中心 📢 【柬埔寨】新闻吃瓜 📢 AI短剧动漫&真人 📢 合肥女奴库 📢 东南亚DJ俱乐部 📢 东南亚时报|柬埔寨大事件|爆料|吃瓜 📢 缅甸缅北吃瓜新闻曝光 📢 吃瓜娱乐资讯🔥 @SSBYQ 📢 东南亚每周刊【曝光】 📢 新闻趣事大曝光 ------------------------------ 🤝 加入互推 · 获得曝光,赚邀请奖励

24 Oct 2026, 14:00 UTC≈1,020 viewsread 25 October 2026
Photo

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24 Oct 2026, 13:41 UTC≈1,030 viewsread 25 October 2026
Video

#马来西亚快讯:吉隆坡 Kingsway 酒吧凌晨移民局突击扫黄,抓了 60 个小姐,还有部分中国人! 最近一直在娱乐场所扫扫扫,大家一定要多加小心。 🕯订阅全网曝光 ↓ 📱@quanwangbaoguang 投稿爆料: @uuuui1

24 Oct 2026, 13:21 UTC9 viewsread 25 October 2026
Photo

此人无签证黑户,山东人,图中NBI抓捕现场,右侧标记的人。锅盖头,脚上有纹身 以前在帕塞赢天下,就多次拿码,同事已经多次取他出来让好好上班,后面骗会员充值到自己账户几万块钱跑路。赌场也跑了马仔的钱,牢里关了几个月。周围能骗的都骗完了。 此人脸皮之厚会叫你爸爸爷爷的求你借钱,应该还在马尼拉 有他详细信息的,和住处的,请联系小编告知,真实的话可以有偿 🕯订阅全网曝光 ↓ 📱@quanwangbaoguang 投稿爆料: @uuuui1

24 Oct 2026, 13:00 UTC≈1,030 viewsread 25 October 2026
Video

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24 Oct 2026, 12:11 UTC8 viewsread 25 October 2026
Photo

#群友爆料:原柬埔寨西港“黄金城园区桥水集团”总监,外号“曹瑞”,广东人,曾在缅甸做总监,国内红通人员。 黄金城被查后,曹瑞带队转移到老挝继续做以色列币盘,后来因检查趋严,又带队转移到乌兹别克斯坦。 团队约20人,大部分人一路跟着曹瑞从柬埔寨到老挝,再到乌兹别克斯坦。当初承诺的福利待遇,却一样没兑现。每月工资700美元,每天工作15小时左右,只要人在职场,就必须坐满18小时。职场里动辄打骂员工,还雇了安保人员。公司搬迁费、租房费和日常运营成本,也全算到员工头上。 曹瑞,这些费用凭什么让员工承担?当初承诺的待遇,又兑现了多少?团队跟着你这么久,真正赚到钱的一个都没有。以色列业务做得一塌糊涂,一波下来,大家连回家过年的机票钱都拿不出来。现在又搞所谓的“接盘票”,天天只知道要数据、要业绩,不管员工会不会做,完不成任务就找理由罚款。业务做成这样,你自己就一点问题都没有吗?罚款能罚出业绩吗?自己没本事做好业务,就知道把压力往员工身上…

24 Oct 2026, 12:00 UTC≈1,020 viewsread 25 October 2026
Video

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24 Oct 2026, 11:41 UTC≈1,010 viewsread 25 October 2026
Video

#网友反馈 西港多名警察组成摩托车队,从西港省警察局出发。目前去向暂不清楚~~ 🕯订阅全网曝光 ↓ 📱@quanwangbaoguang 投稿爆料: @uuuui1

24 Oct 2026, 11:11 UTC≈1,010 viewsread 25 October 2026
Photo

#马来西亚资讯:吉隆坡娱乐场所遭移民局突袭!68名外籍人员被捕,泰国籍人员占多数 马来西亚移民局近日在吉隆坡安普路(Jalan Ampang)一家夜总会展开突击执法行动,共检查113人,并逮捕68名外籍人员,其中包括54名泰国籍人员及14名孟加拉籍人员。 据马来西亚媒体《Utusan Melayu Plus》10月24日报道,此次行动属于移民局开展的“Ops Gegar”执法行动。经过前期约两个月的情报调查及接获民众投诉后,执法人员对涉事娱乐场所实施突击检查。 被捕的68名外籍人员中,包括47名泰国籍女性、7名泰国籍男性,以及14名孟加拉籍男性,年龄介于20岁至55岁之间。 初步调查显示,部分被捕人员虽然持有马来西亚工作准证,但准证所允许从事的工作与其在娱乐场所实际从事的工作不符。例如,持有清洁或建筑行业工作准证的人员,却被发现涉嫌在娱乐场所工作。 马来西亚移民局表示,相关行为涉嫌违反《1963年移民条例》第39(b)…

Showing the 12 most recent of 1,244 posts we hold for @baoguangdashijian. 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.

Posts edited after publishing

@baoguangdashijian edited 1 post after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.

An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.

First edit seen
10 September 2026
Most recent edit
10 September 2026

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.

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 25 October 2026 — this entry's latest reading, not the date you are reading this.

“全网曝光” (@baoguangdashijian), 57,628 subscribers as measured 25 October 2026. Telegram Register, tgregister.com/channel/baoguangdashijian.

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.