🙋🏻♀️东坑 ☎️ 联系方式 电报: @Hlwww67 频道:https://t.me/xiaolidongguang 🏷 分类标签 #东坑 ✳️ 机器人:联系不上群里@她 @dongguanxiuchedadui

Channel
东莞修车大队公开榜
@dongguangongkaibang
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Posts recorded as deleted · Citations · Handles named that no longer answer · Cite this entry
54,121subscribers
+39,081 since we began measuring on 14 August 2026
Risers and fallers across the register · movement among entries of 31,623–100,000.
Register entry
| Telegram ID | -1002345531587 |
|---|---|
| Type | Channel |
| Username | @dongguangongkaibang |
| Description | 交流群:https://t.me/dongguanxiuchedadui |
| Created | Between 1 September 2024 and 31 March 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 14 August 2026 |
| Last confirmed live | 7 November 2026 |
| Measurements held | 54 |
| Confirmed unchanged | 1 time, most recently 7 November 2026 |
| On Telegram | t.me/dongguangongkaibang |
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 59% 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, 11:39 | 54,121 | +423 |
| 6 Nov 2026, 12:46 | 53,698 | +325 |
| 5 Nov 2026, 12:48 | 53,373 | +281 |
| 4 Nov 2026, 14:24 | 53,092 | +477 |
| 3 Nov 2026, 15:56 | 52,615 | +342 |
| 2 Nov 2026, 17:40 | 52,273 | +760 |
| 1 Nov 2026, 16:38 | 51,513 | +432 |
| 31 Oct 2026, 19:10 | 51,081 | +427 |
| 30 Oct 2026, 21:14 | 50,654 | +522 |
| 30 Oct 2026, 00:35 | 50,132 | +481 |
| 28 Oct 2026, 22:49 | 49,651 | +360 |
| 27 Oct 2026, 21:11 | 49,291 | +448 |
| 26 Oct 2026, 21:55 | 48,843 | +423 |
| 25 Oct 2026, 20:18 | 48,420 | +528 |
| 24 Oct 2026, 23:06 | 47,892 | +631 |
| 24 Oct 2026, 01:36 | 47,261 | +597 |
| 23 Oct 2026, 02:49 | 46,664 | +460 |
| 22 Oct 2026, 02:59 | 46,204 | +460 |
| 20 Oct 2026, 21:46 | 45,744 | +609 |
| 19 Oct 2026, 20:07 | 45,135 | first reading |
Engagement
40 posts held, back to 31 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 131 pages of Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 3.82%
- avg views ÷ 54,121 subscribers
- Avg views / post
- 2,070
- 11 posts measured
- Reaction rate
- —
- this channel exposes no reaction counts
- Posts in window
- 11
- of 40 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 6 November 2026 |
|---|---|
| Posts held | 40 (31 July 2026 – 6 November 2026) |
| Views total | 22,765 |
| Reactions total | — |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 8 Nov 2026, 06:24 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
- ≈1,060
- Videos
- ≈193
- Links
- ≈241
Lifetime counters from Telegram’s own channel header, read 8 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.
- Video runtime
- 4m 53s
- Average length
- 13s
Measured directly from 22 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
9 reactions across 4 posts, in 7 distinct kinds. The most used accounts for 33.3% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 3 | 33.3% | |
| 🎉 | 1 | 11.1% | |
| 🏆 | 1 | 11.1% | |
| 😁 | 1 | 11.1% | |
| 🙏 | 1 | 11.1% | |
| 🤩 | 1 | 11.1% | |
| 🥰 | 1 | 11.1% |
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 5 of the 40 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 9 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 40 most recent posts we hold, published 31 July 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).
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Showing the 12 most recent of 40 posts we hold for @dongguangongkaibang. 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 4 posts on @dongguangongkaibang 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
- 22 October 2026
- Most recent seen missing
- 6 November 2026
- Median time before seen missing
- 3 days
- Seen missing in the last 30 days
- 4
Mentions
Names
Channels on the register whose handles appear in this channel's posts.
@dongguanxiuchedadui · 62,12514 posts东莞惠州顶级丝足口爆会所TOP1
@dongguanhuizhou999 · 5,5953 posts山鸡深圳中高端 大圈
@Bdhjfvf88 · 3,0612 posts诗末的小区🏠
@dlsy520 · 6872 posts东莞塘厦姐妹团公开榜
@hhfyjjbv5858 · 53,9422 posts安安慕南专属男宠宝贝们的小家
@Jjkkhhhkjhh · 4,9322 posts东莞裸身抚触抓龙筋SPA
@szchujianSPA · 3,3752 posts山鸡东莞市区高端看图💒可外
@TMXBBX · 5032 posts深圳全区 平价车 4~6米
@xbjktd88 · 2,1302 posts山鸡 长安高端群
@XBOK66 · 1,3392 posts东莞小丽个人工作室
@xiaolidongguang · 1,0182 posts东莞东城 叶子楣的小屋🏠
@ABC168BB · 1,5021 post东莞快餐➕高端
@dgnbbdjurbt9 · 2,8731 post全国莞式全套会所
@mili0289 · 11 post揭阳盼盼的小花园
@qian82 · 2171 post东莞惠州94会所海选专场
@Qqm666888 · 3,5271 post塘厦🌸欣欣🌸🉑69
@r65444 · 6251 post半醺的闺房💋
@shuiduoduo678 · 3891 post小妍的宝宝
@xiaoyanbao19 · 1,2861 post希儿大宝贝❤️❤️❤️
@xier168168168 · 1,3931 postJoan
@xxxbbb998 · 11 post抓龙筋频道
@y15281 · 1,3261 post颜兮的后花园
@yanxi111223 · 661 post东莞园洲大型水疗会所94
@yzywaz · 191 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.
Handles this channel named that no longer answer
- Dead references
- 1
- handles named in this channel’s posts, vacant today
- Evidenced gone
- 0
- we ourselves saw one of these resolve, at some point
- Never seen alive
- 1
- vacant every time we have ever looked
@dongguangongkaibang named 1 handle 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.
Never seen alive
References a handle that is not a live channel — we have no record it ever was one.
named in 2 posts, 9 October 2026 – 11 October 2026
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.
“东莞修车大队公开榜” (@dongguangongkaibang), 54,121 subscribers as measured 7 November 2026. Telegram Register, tgregister.com/channel/dongguangongkaibang.
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.