这位妈妈丝毫不觉得她教育出现问题了嘛
👍1

Channel
@baguabox
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Telegram's recommendations · Cite this entry
33,173subscribers
-293 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 31,623–100,000.
| Telegram ID | -1001228673671 |
|---|---|
| Type | Channel |
| Username | @baguabox |
| Description | 吃瓜 八卦 黑幕 黑料 广告联系 @haobangdada 小火箭chatgpt gv gmail tg独享 app兑换码 @yangwangshop 羊毛频道 @yangwangpindao |
| Created | 1 November 2019 — measured — cross-checked against a third-party dataset (TGDataset) |
| First recorded | 6 August 2026 |
| Last confirmed live | 1 November 2026 |
| Measurements held | 55 |
| Confirmed unchanged | 1 time, most recently 1 November 2026 |
| On Telegram | t.me/baguabox |
Gambling & betting — 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 99% 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 |
|---|---|---|
| 1 Nov 2026, 08:17 | 33,173 | -17 |
| 31 Oct 2026, 06:08 | 33,190 | -5 |
| 30 Oct 2026, 02:29 | 33,195 | -5 |
| 29 Oct 2026, 02:48 | 33,200 | -15 |
| 28 Oct 2026, 00:05 | 33,215 | -4 |
| 27 Oct 2026, 00:46 | 33,219 | -5 |
| 25 Oct 2026, 21:16 | 33,224 | -4 |
| 24 Oct 2026, 20:56 | 33,228 | +2 |
| 23 Oct 2026, 21:40 | 33,226 | -4 |
| 22 Oct 2026, 23:16 | 33,230 | -14 |
| 21 Oct 2026, 21:48 | 33,244 | +3 |
| 20 Oct 2026, 19:07 | 33,241 | -9 |
| 19 Oct 2026, 21:00 | 33,250 | -3 |
| 18 Oct 2026, 20:09 | 33,253 | -5 |
| 17 Oct 2026, 23:39 | 33,258 | -22 |
| 17 Oct 2026, 02:00 | 33,280 | -8 |
| 16 Oct 2026, 01:28 | 33,288 | -7 |
| 13 Oct 2026, 20:06 | 33,295 | -9 |
| 10 Oct 2026, 09:01 | 33,304 | -30 |
| 6 Oct 2026, 04:01 | 33,334 | first reading |
2,159 posts held, back to 5 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 156 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 272 of 854 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 1 November 2026 |
|---|---|
| Posts held | 2,159 (5 August 2026 – 1 November 2026) |
| Views total | 293,970 |
| Reactions total | 375 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 1 Nov 2026, 18:44 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 1 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 846 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.
430 reactions across 285 posts, in 21 distinct kinds. The most used accounts for 65.8% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 👍 | 283 | 65.8% | |
| ❤ | 55 | 12.8% | |
| 😁 | 23 | 5.35% | |
| 🤣 | 12 | 2.79% | |
| 👏 | 11 | 2.56% | |
| 💩 | 7 | 1.63% | |
| 🔥 | 5 | 1.16% | |
| 🤩 | 5 | 1.16% | |
| 🌚 | 4 | 0.93% | |
| 🎉 | 4 | 0.93% | |
| 🥰 | 4 | 0.93% | |
| 😢 | 3 | 0.698% | |
| 🤡 | 3 | 0.698% | |
| 💅 | 2 | 0.465% | |
| 🤔 | 2 | 0.465% | |
| 🤪 | 2 | 0.465% | |
| ❤🔥 | 1 | 0.233% | |
| 🌭 | 1 | 0.233% | |
| 🖕 | 1 | 0.233% | |
| 😨 | 1 | 0.233% | |
| 1 further kind | 1 | 0.233% |
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 311 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 430 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 27 September 2026 to 1 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.
这位妈妈丝毫不觉得她教育出现问题了嘛
👍1
车位大战,后面的车多少有点不地道!
👍1
谈对象就要1米8以上,8块腹肌的,这种打人最疼了!
👍1👏1
从小培养女儿跳舞的家长陷入了深深的沉思!
👍1
正所谓好男不和女争,好在保安大哥比较克制!
👍1
今年万圣节最佳COS!
她穿白丝还戴眼镜,这个时候她说什么都是对的!
北大禁烟女战士,拍视频曝光劝阻他人吸烟
已引退定居香港的前日本女优滨崎真绪,万圣节当晚在尖沙咀私人场所打碟时疑似遭人下药。 当晚她结束工作后,被对方多次劝说转场演出,经纪人再三推脱无果只能妥协。 现场玩游戏罚酒期间,她喝下多杯酒水,凌晨又饮用陌生人递来的饮品,随后迅速神志不清。 事后她突发全身抽筋、身体瘫痪,紧急送医进ICU抢救,体内检测出四种违禁药物。经纪人极度自责,目前已报警交由警方调查。
今天凌晨2点,这司机干啥呢
一段视频在澳大利亚引热议! 一个澳大利亚人披着澳大利亚国旗进入图书馆,被印度人移民拦着不让进入。 这一幕激起澳大利亚本土民众的排外情绪!
😁1
还在为找资源头疼吗? 满屏广告、假链接、下载半天打开是病毒…… 受够了没? 现在有个懒人神器 👉 @cilisearch_bot 直接输入你想看的片名 / 资源关键词,秒出结果,点一下就能在线预览播放 ✅ 磁力搜索 秒级响应 ✅ 一键预览 边看边定 ✅ 无广告骚扰 干净利落 找片不迷路,认准 👉 @cilisearch_bot
Showing the 12 most recent of 2,159 posts we hold for @baguabox. 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.
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Republishes
Channels on the register whose posts this channel has forwarded.
Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.
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 4 September 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 10 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 1 November 2026 — this entry's latest reading, not the date you are reading this.
“TG吃瓜黑料八卦” (@baguabox), 33,173 subscribers as measured 1 November 2026. Telegram Register, tgregister.com/channel/baguabox.
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.