以后哪个老师需求更新重新发榜单。 可以,给钱。天天这个要重新挂榜,那个要更新资料的,群里没有这个义务,跟上其他群的节奏,,不然别人嘲讽鄙视的。,
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Channel
@bigwuhangk
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Posts edited after publishing · Citations · Handles named that no longer answer · Cite this entry
26,881subscribers
-272 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 10,000–31,623.
| Telegram ID | -1001224822967 |
|---|---|
| Type | Channel |
| Username | @bigwuhangk |
| Created | Between 1 March 2018 and 31 July 2021 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 19 September 2026 |
| Measurements held | 32 |
| Confirmed unchanged | 1 time, most recently 19 September 2026 |
| On Telegram | t.me/bigwuhangk |
Education — 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 10 September 2026 and assigned it the closest of 31 fixed categories, at 37% 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 |
|---|---|---|
| 19 Sept 2026, 15:38 | 26,881 | -12 |
| 17 Sept 2026, 00:19 | 26,893 | -12 |
| 15 Sept 2026, 01:00 | 26,905 | -21 |
| 13 Sept 2026, 13:20 | 26,926 | -5 |
| 9 Sept 2026, 11:16 | 26,931 | -2 |
| 6 Sept 2026, 02:19 | 26,933 | -9 |
| 3 Sept 2026, 21:40 | 26,942 | -6 |
| 2 Sept 2026, 12:03 | 26,948 | -2 |
| 1 Sept 2026, 14:44 | 26,950 | -4 |
| 31 Aug 2026, 15:57 | 26,954 | -4 |
| 30 Aug 2026, 15:07 | 26,958 | -2 |
| 29 Aug 2026, 14:27 | 26,960 | -12 |
| 28 Aug 2026, 11:55 | 26,972 | -29 |
| 27 Aug 2026, 08:32 | 27,001 | -16 |
| 26 Aug 2026, 06:38 | 27,017 | -11 |
| 25 Aug 2026, 03:02 | 27,028 | -9 |
| 23 Aug 2026, 19:18 | 27,037 | +44 |
| 22 Aug 2026, 00:35 | 26,993 | -2 |
| 20 Aug 2026, 16:03 | 26,995 | +2 |
| 19 Aug 2026, 18:08 | 26,993 | first reading |
48 posts held, back to 13 July 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 62 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 12 of 17 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 1 September 2026 |
|---|---|
| Posts held | 48 (13 July 2026 – 1 September 2026) |
| Views total | 17,933 |
| Reactions total | 32 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 3 Sept 2026, 09:57 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.
Measured directly from 1 video 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.
251 reactions across 35 posts, in 10 distinct kinds. The most used accounts for 34.7% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 87 | 34.7% | |
| 👍 | 71 | 28.3% | |
| 👏 | 24 | 9.56% | |
| 🔥 | 20 | 7.97% | |
| 🎉 | 18 | 7.17% | |
| 🥰 | 18 | 7.17% | |
| 🤬 | 7 | 2.79% | |
| 😢 | 3 | 1.20% | |
| 🤔 | 2 | 0.797% | |
| 😁 | 1 | 0.398% |
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 39 of the 48 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 251 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 48 most recent posts we hold, published 13 July 2026 to 1 September 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.
以后哪个老师需求更新重新发榜单。 可以,给钱。天天这个要重新挂榜,那个要更新资料的,群里没有这个义务,跟上其他群的节奏,,不然别人嘲讽鄙视的。,
😢1
9月 老师轮播名单,可以推荐啦。 15000分兑换哦😍😍😍😍😍😍😍😍😍😍 快拿出你的积分来兑换吧,给你喜欢的老师打CALL😍😍😍🥰 1: 该老师的一张宣传照片 和老师的 @用户名 2:一段关于老师的宣传文案,可以是课表内容也可以是心情文案,随便你哦 3: 提交之前要考虑好,已经设置了就无法更改了,不然我们因为你一句话可能得折腾半小时。 4:15000积分兑换一个月,不设置名额。 也不限制你推荐几个老师,你分够你就来。 推荐私聊 @wuhancn_bot
@XiaomengGroupBot 以后老师自己跟 易查询机器人对话 输入开课 每天要输入, 以后老师打卡实时群 由管理员根据老师输入的 实时打卡信息,公布地区,价格 ,老师名单。 https://t.me/whlsdaka 这是老师打卡群,以后由管理员输入 实时有效信息,你不跟机器人对话输入开课 就没有名单。 管理每天实时在群里更新榜单。
双向解封跟申诉方法 Ⅰ:普通双向 会员用户秒解 👉第一步: @spambot 👉第二步: Start (点两次) Ⅱ:无限期永封需要申诉(非会员也可以用) 👉第一步: @spambot 👉第二步: Start 👉第三步:第四个按钮 👉第四步: YES(第一个按钮) 👉第五步: NO(第一个按钮) 👉第六步:写小作文 一次解不开多解几次,每次用不同的文本。下面几个例子的基础上 添油加醋发挥我的文采,你一年的申诉聊天记录是30多次,丰富的斗争经验告诉你,只要文本多 只要申诉的多 完全可以解开(点击字体复制) 例子 1 :I only use this software to chat with friends. If there is a wrong ban, please help me unblock it. I will also abide by the rules in the future 例子 2 :I …
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别想着炸群了,,,,,,,,,,,,,,,,,,,你没那能力的。。以前你也炸不了。 现在更别想了。。。。。。。死了那个心吧。。。 都几年前的水平了,现在拿出来用, 跟小丑一样。。。。。。。。 我打出这段话,都觉得好难堪。。。。
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https://t.me/whlsjcheping 新得老师打卡群 就是之前的车评群,原先的老师打卡群是私密群,无法更改,所以换成了公开群。 就是两个群对换了下,什么都没变 原先的老师打卡群变成了车评群 车评群变成了打卡群 仅仅如此而已。。
@xi455555 夕夕 注意防骗,可能号在代聊手里, 想骗一波跑路 。。群友到了位置不开门,要求先给500客费。 本群目前不支持老师收定金, 要定得不要去。 不要转账,不要约课,。。。请注意
数据还在迁移当中。 完成了之后会让符合条件的老师 申请的。 此外 老师打卡群 迁移到车评群 ,https://t.me/whlsjcheping 这是公开群,为了以后挂搜索排名准备 意思 就是车评群变成 老师打卡群, 老师打卡群 变成 车评群, 两个群互换了而已,什么都没变哈。。 不需要任何老师提供资料跟课表,这里都有。
排名奖励已经发送完毕, 小尾巴还是多辛苦下, 看看那些诈骗粉哈,。。 保护群友财产安全有大家辛勤得付出😆😆😄😁😁😁 下个月择机依旧持续。
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🌟总分排行榜🌟 11、周 周 - 4986 12、小十 - 4710 13、夏天(开4P/6PP营业中) - 3015 14、十二(红休)🫧🫧 - 2886 15、八戒不近女色 - 2745 16、格格 洪山区 莞式系(开课🀄️) - 2066 17、夏天也温柔 Hoshiko - 2046 18、服务系3️⃣通午夜🉑sm😘可剧情🫦🉑夜 - 1803 19、江南第二深情🏎️ - 1737 20、大佐(岸) - 1676 当前页码:2/336
🌟总分排行榜🌟 1、阿明🤑 (所长) - 5412 2、303(清晨的粥) - 5400 3、紫川 - 5367 4、马里奥 - 5178 5、浮光 - 5167 6、王麻子 - 5153 7、雾一 - 5152 8、陈 冠希 - 5100 9、九亿少妇的梦 - 5100 10、情绪的主人 - 5090 当前页码:1/336
❤1👍1👏1🔥1
下个月专榜不使用了,不在更新了,数据都平移到了 https://t.me/whzygxq 这个频道了 以后请关注下面精品老师频道。 https://t.me/whjingpinls 1:好评报告超过20份,必须是个人自聊老师,在本群独家挂榜的老师,满足条件即可申请。 2:接受设备机器人的抽查,每天24小时无死角检测,不接受代聊中介挂精品老师榜。 3:中介代聊就在公开榜跟新人榜开吧,你过不了机器人的检测验证浑水摸鱼不了的,不要因小失大的,躲不过去的, 4:专榜的数据平移了以后,这个专榜封存,当作备用频道,哪天炸了个频道,无缝切换顶上去。 5:为啥不用专榜了,因为私密频道跟群,无法更好的展示,这个频道是公开频道,并且收录了,以后会花点时间上搜索第一页的,为了更好的展示你们老师的资料,大环境不好,能多帮助你们老师展示一下渠道就多帮助一分,闭门造车始终不是长久之计的,你们老师也需要展示跟浏览。 6:中文圈子都以搜索粉为荣,以排名…
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Showing the 12 most recent of 48 posts we hold for @bigwuhangk. 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.
@bigwuhangk edited 11 posts 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.
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
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.
@bigwuhangk named 2 handles that resolve to nothing today. That is a fact about the reference, not necessarily a fact about the handle’s history — see the two groups below.
Most of these may never have existed as a live channel at all. A handle a channel names can be a typo, an aspirational name nobody registered, or a channel that was already gone before this one ever mentioned it. Unless a row below is marked evidenced, all we know is that it references a handle that is not a live channel today — not that anything “died”. How this is measured.
We ourselves saw each of these resolve to a real page at some point before it went vacant — a genuine, evidenced change, not an inference from absence.
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 19 September 2026 — this entry's latest reading, not the date you are reading this.
“武汉公开榜” (@bigwuhangk), 26,881 subscribers as measured 19 September 2026. Telegram Register, tgregister.com/channel/bigwuhangk.
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.