【排雷报告】https://t.me/guangfoyongle2020 【所有位置】金沙洲 【老师艺名】#夏沫 【联系方式】@xiamo2007 【人照几成】7成 【中介代聊】是 【上课价位】注:600 【服务情况】口活有齿感,下面有点松,屌感不太好,做爱的时候还会拿腿顶住你不让你深入,整体下来感觉一般 【雷点说明】不像嫩妹,身材像生育过,下面有点松且死鱼,没有服务,除了胸一无是处 PS排雷原因:中介代聊,符合排雷条件,永乐群已永久下榜拉黑,排雷奖励200元已经发放,排雷奖励188永乐通宝已经到账,辛苦工兵排雷致敬🫡

Channel
广州佛山黑车防爆
@heichefangbao
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
12,429subscribers
+936 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 10,000–31,623.
Register entry
| Telegram ID | -1002170965618 |
|---|---|
| Type | Channel |
| Username | @heichefangbao |
| Created | Between 1 June 2024 and 30 September 2024 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 7 November 2026 |
| Measurements held | 61 |
| Confirmed unchanged | 2 times, most recently 7 November 2026 |
| On Telegram | t.me/heichefangbao |
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 11 September 2026 and assigned it the closest of 31 fixed categories, at 80% 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 |
|---|---|---|
| 6 Nov 2026, 01:09 | 12,429 | -2 |
| 5 Nov 2026, 01:58 | 12,431 | -5 |
| 4 Nov 2026, 02:30 | 12,436 | -12 |
| 3 Nov 2026, 00:41 | 12,448 | -47 |
| 1 Nov 2026, 21:59 | 12,495 | -3 |
| 31 Oct 2026, 21:21 | 12,498 | +3 |
| 30 Oct 2026, 23:28 | 12,495 | -5 |
| 30 Oct 2026, 00:46 | 12,500 | +8 |
| 28 Oct 2026, 23:31 | 12,492 | -10 |
| 27 Oct 2026, 20:17 | 12,502 | -3 |
| 26 Oct 2026, 20:16 | 12,505 | -12 |
| 25 Oct 2026, 21:27 | 12,517 | -7 |
| 24 Oct 2026, 19:38 | 12,524 | -4 |
| 23 Oct 2026, 21:17 | 12,528 | -5 |
| 22 Oct 2026, 19:47 | 12,533 | -7 |
| 21 Oct 2026, 17:51 | 12,540 | -22 |
| 20 Oct 2026, 13:17 | 12,562 | -21 |
| 19 Oct 2026, 14:00 | 12,583 | -5 |
| 18 Oct 2026, 14:59 | 12,588 | -13 |
| 17 Oct 2026, 17:21 | 12,601 | first reading |
Engagement
21 posts held, back to 8 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 59 pages of Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 23.6%
- avg views ÷ 12,429 subscribers
- Avg views / post
- 2,940
- 4 posts measured
- Reaction rate
- 0.141%
- reactions ÷ views · ER floor
- Posts in window
- 6
- of 21 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 3 of 4 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 | 21 (8 July 2026 – 6 November 2026) |
| Views total | 11,740 |
| Reactions total | 14 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 7 Nov 2026, 19:28 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
- 891
- Videos
- 1
- Links
- 92
Lifetime counters from Telegram’s own channel header, read 7 November 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.
Reaction mix
54 reactions across 8 posts, in 6 distinct kinds. The most used accounts for 44.4% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 24 | 44.4% | |
| 🤣 | 21 | 38.9% | |
| 💩 | 4 | 7.41% | |
| 👍 | 2 | 3.70% | |
| 👏 | 2 | 3.70% | |
| 🤡 | 1 | 1.85% |
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 21 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 54 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 21 most recent posts we hold, published 8 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 6 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).
【排雷报告】https://t.me/guangfoyongle2020 【所有位置】四季红威尼酒店 【老师艺名】#景瑶 【联系方式】@Jjingyaoa 【人照几成】没见到 【中介代聊】注:是 【上课价位】注:600:中介代聊、人照不符 【服务情况】到了以后要安排其他的 【雷点说明】注:中介代聊、人照不符 PS排雷原因:中介代聊,符合排雷条件,永乐群已永久下榜拉黑,排雷奖励200元已经发放,排雷奖励188永乐通宝已经到账,辛苦工兵排雷致敬🫡
❤2
广州佛山黑车防爆 pinned a photo
【排雷报告】https://t.me/guangfoyongle2020 【所有位置】金沙洲 【老师艺名】#刘薇 【联系方式】@liuwei3331 【人照几成】8 【中介代聊】是 【上课价位】800 【服务情况】无服务 很不耐烦 切不会和你有任何沟通 【雷点说明】 上楼留门进入 老师坐着就玩手机 先交钱 然后才开始说没有陪洗澡 我说但是服务上有的 很不情愿陪洗 非常不舒服,冷漠加不说话 浴巾什么都是自助 接着就是开始服务 基本什么都没有 吹做 而已 非常扫兴 速度结束 全程不说话 只有自己动手 老师一直就是看手机玩手机看视频 不交流? 快餐就快餐别挣服务的钱 挂羊头卖狗肉 有钱兄弟们也没必要花到这种地方 cj多次 头一次被恶心到了。 花钱买脸色 何必呢… 而且老师自己说了是别人代聊 没有账号 所以很敷衍 态度极差 花这个钱就为了写这个报告 真的恶心 PS排雷原因:中介代聊,符合排雷条件,永乐群已永久下榜拉黑,排雷奖励200…
❤7
广州佛山黑车防爆 pinned a photo
【排雷报告】https://t.me/guangfoyongle2020 【所有位置】黄埔 【老师艺名】#白雪 【联系方式】@xxbb629 【人照几成】8 【中介代聊】疑是 【上课价位】500p 【服务情况】没服务 【雷点说明】假波没服务,没陪洗、没kiss(说亲一下加100)、戴套口,舔两下胸戴套口一下就插上来了,女上位一下就说痛换传教式,中途想换姿势后入又阻止不给,说有规矩插进去不能拔出来,像中介代聊,不知道电报是什么,就一个臭鸡嫩妹 PS排雷原因:中介代聊,符合排雷条件,永乐群已永久下榜拉黑,排雷奖励200元已经发放,排雷奖励188永乐通宝已经到账,辛苦工兵排雷致敬🫡
❤3👍2
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❤1
【排雷报告】https://t.me/guangfoyongle2020 【所有位置】金沙洲 【老师艺名】#晶晶 【联系方式】@miaomiao1600 【人照几成】6.5 【中介代聊】是 【上课价位】5P 【服务情况】课表除了吹,其他都没有 【雷点说明】中介代聊情况,明明在上课时间,老师的空间竟然更新了优惠夜课消息,课表内容不知情 PS排雷原因:中介代聊,符合排雷条件,永乐群已永久下榜拉黑,排雷奖励200元已经发放,排雷奖励188永乐通宝已经到账,辛苦工兵排雷致敬🫡
Telegram必备的搜索引擎,极搜JISOU帮你精准找到,想要的群组、频道、视频、音乐 👉 t.me/jisou2?start=a_209174135
Telegram必备的搜索引擎,极搜JISOU帮你精准找到,想要的群组、频道、视频、音乐 👉 t.me/jisou2?start=a_209174135
Telegram必备的搜索引擎,极搜JISOU帮你精准找到,想要的群组、频道、视频、音乐 👉 t.me/jisou2?start=a_209174135
Showing the 12 most recent of 21 posts we hold for @heichefangbao. 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 3 posts on @heichefangbao 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
- 12 August 2026
- Median time before seen missing
- 2 days
- Seen missing in the last 30 days
- 0
Forward network
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.
Mentions
Named by 15 registered channels — 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.
@baiyun95didi · 3,1631 post佛山高质量94(一号店XC会所)
@fscc9444 · 2111 post广州佛山永乐公开榜
@guangfoyongle · 51,9971 post筱萍🉐️爱窝❤️
@kekeai666 · 1621 post天河 困困de小家
@kunkun80 · 6631 post海珠丽丽小窝
@lili943400z · 1,1901 post🦋Lisa·球球的小窝🏠
@Lisathelittlefairyisworkinghard · 3,0231 post浅浅的私密分享空间
@meixiBB · 1,1041 post娜娜🍒的朋友圈
@mina52016899 · 5351 post🫧泡泡🐟亲测报告
@ppyhs3 · 3,9721 post🌸兔子的家人们🐰
@tuzidejiarenmen · 3,8481 post小小❤️小屋
@xiaoxiao720 · 1,8521 post【广州】Ym·Mens相册&报告
@xyspa111 · 3,1431 post【广州】Ym·Mens【亲测报告】
@xyspa1111 · 2,5271 post白云梅花园洋洋空间
@y1666999 · 1,5011 post
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.
Handles this channel named that no longer answer
- Dead references
- 1
- handles named in this channel’s posts, vacant today
- Evidenced gone
- 1
- we ourselves saw one of these resolve, at some point
- Never seen alive
- 0
- vacant every time we have ever looked
@heichefangbao 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.
Evidenced gone
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.
named in 2 posts, 8 August 2026 – 9 August 2026 · confirmed gone 13 October 2026 (two independent sightings — see how we confirm a dead handle)evidenced
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 6 November 2026 — this entry's latest reading, not the date you are reading this.
“广州佛山黑车防爆” (@heichefangbao), 12,429 subscribers as measured 6 November 2026. Telegram Register, tgregister.com/channel/heichefangbao.
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.