🌈 🫂广州交流群组 ✅广州认证资源

Channel
广州911报告📮
@ZhangWaog
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Posts recorded as deleted · Citations · Cite this entry
17,663subscribers
-1,764 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 10,000–31,623.
Register entry
| Telegram ID | -1001325739597 |
|---|---|
| Type | Channel |
| Username | @ZhangWaog |
| 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 | 7 November 2026 |
| Measurements held | 59 |
| Confirmed unchanged | 1 time, most recently 7 November 2026 |
| On Telegram | t.me/ZhangWaog |
Topic
Other / unclassifiable — 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 74% 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.
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 7 Nov 2026, 08:56 | 17,663 | -33 |
| 6 Nov 2026, 05:51 | 17,696 | +11 |
| 5 Nov 2026, 05:51 | 17,685 | +27 |
| 4 Nov 2026, 06:31 | 17,658 | +24 |
| 3 Nov 2026, 03:49 | 17,634 | +37 |
| 2 Nov 2026, 05:06 | 17,597 | +28 |
| 1 Nov 2026, 03:26 | 17,569 | +29 |
| 31 Oct 2026, 01:49 | 17,540 | -66 |
| 30 Oct 2026, 01:41 | 17,606 | -2 |
| 29 Oct 2026, 00:58 | 17,608 | +34 |
| 28 Oct 2026, 00:17 | 17,574 | -27 |
| 27 Oct 2026, 01:16 | 17,601 | +41 |
| 26 Oct 2026, 01:36 | 17,560 | -12 |
| 25 Oct 2026, 03:37 | 17,572 | -1 |
| 24 Oct 2026, 01:40 | 17,573 | -570 |
| 22 Oct 2026, 22:10 | 18,143 | -17 |
| 21 Oct 2026, 21:37 | 18,160 | +4 |
| 20 Oct 2026, 16:14 | 18,156 | -32 |
| 19 Oct 2026, 15:46 | 18,188 | +3 |
| 18 Oct 2026, 18:07 | 18,185 | first reading |
Engagement
73 posts held, back to 24 March 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 67 pages of Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 0.89%
- avg views ÷ 17,663 subscribers
- Avg views / post
- 157
- 11 posts measured
- Reaction rate
- 0%
- reactions ÷ views · ER floor
- Posts in window
- 11
- of 73 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 1 of 11 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 6 November 2026 |
|---|---|
| Posts held | 73 (24 March 2026 – 6 November 2026) |
| Views total | 1,730 |
| Reactions total | 0 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 7 Nov 2026, 04:05 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
- 47s
- Average length
- 12s
Measured directly from 4 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
11 reactions across 8 posts, in 1 kind.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 11 | 100.0% |
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 9 of the 73 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 11 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 73 most recent posts we hold, published 24 March 2026 to 6 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.
Recent posts
Telegram’s own ‘edited’ marker: 0 of 11 posts held from the last 30 days (0%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).
🌈 🫂广州交流群组 ✅广州认证资源
🌈 🫂广州交流群组 ✅广州认证资源
🌈 🫂广州交流群组 ✅广州认证资源
🌈 🫂广州交流群组 ✅广州认证资源
🌈 🫂广州交流群组 ✅广州认证资源
🌈 🫂广州交流群组 ✅广州认证资源
🌈 🫂广州交流群组 ✅广州认证资源
🌈 🫂广州交流群组 ✅广州认证资源
(报告模板) 【老师艺名】奶汐 【联系方式】@nx8815 【上课地址】天河车陂 【上课价位】400p 【验证留名】小魔王 【验证时间】10.27 【颜值身材】身材苗条,丰满,人照基本一致 【服务内容】课表都有 【服务态度】10 【优点缺点】非常好的老师 【体验细节】看了好几个老师,都是一言难尽,最后还是选择了奶汐老师,进门便看到老师穿着性感的战袍,养精蓄锐三天三夜的弟弟瞬间被唤醒,顺势把手伸进胸襟中抚摸着想念已久的手感,交完水费,老师看到我顶起来后直接扒开我的裤子“好大好喜欢哦”,一边亲一边进入浴室,沐浴时巴不得把全身都舔个遍 浴室出来后,我直接把老师推倒在沙发上,掰开她的小穴舔舐起来,没过一会就开始听到优美的喘息声,大腿也随着微微夹紧,应该是快受不了了,轮到她攻守易型反过来开始舔我的,真的好会,蛋蛋,大腿两侧,龟头……憋了这么久我开始有点忍不住直接在沙发上开始了,传教士姿势每冲刺一下就与老师的舌尖缠绕在一起,接着又去到卧室,…
(报告模板) 【老师艺名】奶汐 【联系方式】@nx8815 【上课地址】天河车陂 【上课价位】400p 【验证留名】海哥 【验证时间】10.23 【颜值身材】身材苗条,人照基本一致 【服务内容】69,蛇吻,毒🐲,水箫,深喉,课表都会配合 【服务态度】10 【优点缺点】老师服务一流,不催,态度热情,很哇塞 【体验细节】频道看到老师就想试试,按照老师指导上楼,一进门看见老师很满意没有让我,人和照片都这样,身材标准我喜欢,特别有味道,笑起来甜蜜蜜的,跟老师一起洗澡然后在浴室让老师给我口了一下不得不说口活惊艳到我了,那小嘴巴一吞一吐让我的牛子爽飞了,差点交枪太舒服了。在床上又享受了一下老师的口技后面实在被舔的受不了了,掰开一看粉嫩丝滑,水汪汪的小穴,吃起来没有异味,老师也特别享受,两腿颤抖,还发出了爽的声音,看来老师也是享受之人,鸡吧硬得不行,换老师口,蹲式舔,老师拿舌头从蛋蛋根部打转,眼神还不停的目视我,销魂的不要不要的。龟头旋转卷,…
【老师艺名】广州天河95高质量课堂 【联系方式】 @Xiexie580 【上课地址】东圃 【上课价位】800 【验证留名】南来北往zz 【验证时间】26.10.1 【颜值身材】翘臀,好腰! 【服务内容】菜单的服务,做得很多 【服务态度】非常到位! 【优点缺点】烧烧的 【体验细节】放假老子就不去和别人堵了,还是去爽一下合适。今天挑了个新店,去体验一下服务如何。天气真特么热,还好提前预约好直接到店。进房接待立马递上冰镇快乐水,这口值了!坐了一下,老师敲门进来,操!这老师穿个蕾丝半透装,奶头都快露出来了,骚死!还说啥,就她了呗!得到同意老师就去给我铺床了,一弯腰,嘶……这,这老师的裙底下连内裤都没穿,狗日啊老师……你害我内裤都被前列腺液弄湿了……有你这么骚气的吗🤣好好好。洗完上床,一边享受服务一边和老师聊起天来,那撩人的话,都快骚断腿了要。而且这老师的技术很好啊,舌头会绕,会刮,会顶,特么的真心顶不住!!!爽到顶就直接摁着头全喷她嘴…
❤1
Showing the 12 most recent of 73 posts we hold for @ZhangWaog. 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 recorded as deleted after publishing
We recorded 5 posts on @ZhangWaog as deleted — posts this register held that were missing from the channel’s public page on two separate reads, taken from different network addresses at least an hour apart.
A deletion is not wrongdoing. This register can see that a post it held is no longer on the channel’s public page, and when — not why. Expired ad placements, reposts, rotating links and corrections all look the same. This is a count of recorded detections, not an exact total: it misses deletions we could not see, because only a post we held and later re-read inside the page can be seen to go, and it may include a small number of wrong records. How this is measured.
- First seen missing
- 8 August 2026
- Most recent seen missing
- 11 August 2026
- Median time before seen missing
- 19 hours
- Seen missing in the last 30 days
- 0
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.
@Hzxiaomo · 41,88364 posts广州修车911
@xiaokanQ · 62,70660 posts🎁免费抽奖助手🎁
@tgLotteryuw8bot · 13,0175 postsTelegram抽奖活动
@xiu8che · 99,4345 posts广州05二次元小魔女花园🔥🔥🔥
@dcnil19 · 9,6421 post广州04年花店老板娘38D🌹
@huad80 · 18,5521 post广深佛【中高端外围】🥇
@ooggggggggg · 1,1841 post禅城区06年书瑶开课专区❤️🔥
@ryyn168 · 4,4391 post07年小不点校园圈
@xiaobudian0071 · 5,1581 post广州模特瑶瑶私密窝38E
@yy168d · 11,3291 post
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 7 November 2026 — this entry's latest reading, not the date you are reading this.
“广州911报告📮” (@ZhangWaog), 17,663 subscribers as measured 7 November 2026. Telegram Register, tgregister.com/channel/ZhangWaog.
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.