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Channel

然后业务频道

@ranhoupingdao

On this record: Topic · Growth · Engagement · Reactions · Posts · Posts edited after publishing · Citations · Cite this entry

8,091subscribers

-6,921 since we began measuring on 14 August 2026

Risers and fallers across the register · movement among entries of 3,162–10,000.

Register entry

Telegram ID-1003744564700
TypeChannel
Username@ranhoupingdao
CreatedBetween 1 February 2026 and 1 July 2026 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded14 August 2026
Last confirmed live15 November 2026
Measurements held48
Confirmed unchanged1 time, most recently 15 November 2026
On Telegramt.me/ranhoupingdao

Topic

Hacking & security — 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 96% 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

8,09115,01311,55214 August 2026 — 15,012 subscribers15 August 2026 — 15,013 subscribers16 August 2026 — 15,010 subscribers17 August 2026 — 15,009 subscribers18 August 2026 — 15,011 subscribers19 August 2026 — 14,986 subscribers20 August 2026 — 14,922 subscribers21 August 2026 — 14,893 subscribers23 August 2026 — 14,823 subscribers24 August 2026 — 14,745 subscribers25 August 2026 — 14,706 subscribers26 August 2026 — 14,563 subscribers27 August 2026 — 14,539 subscribers28 August 2026 — 14,455 subscribers29 August 2026 — 14,316 subscribers30 August 2026 — 14,247 subscribers31 August 2026 — 14,194 subscribers1 September 2026 — 14,109 subscribers2 September 2026 — 14,036 subscribers3 September 2026 — 13,945 subscribers5 September 2026 — 13,734 subscribers9 September 2026 — 13,515 subscribers11 September 2026 — 13,313 subscribers13 September 2026 — 13,166 subscribers15 September 2026 — 13,054 subscribers17 September 2026 — 12,934 subscribers19 September 2026 — 12,718 subscribers26 September 2026 — 12,400 subscribers4 October 2026 — 12,151 subscribers9 October 2026 — 11,772 subscribers13 October 2026 — 11,348 subscribers14 October 2026 — 11,201 subscribers15 October 2026 — 11,094 subscribers16 October 2026 — 11,056 subscribers17 October 2026 — 10,807 subscribers18 October 2026 — 10,718 subscribers19 October 2026 — 10,638 subscribers20 October 2026 — 10,486 subscribers21 October 2026 — 10,380 subscribers22 October 2026 — 10,210 subscribers24 October 2026 — 10,096 subscribers25 October 2026 — 9,927 subscribers28 October 2026 — 9,514 subscribers31 October 2026 — 9,027 subscribers2 November 2026 — 8,870 subscribers6 November 2026 — 8,746 subscribers9 November 2026 — 8,525 subscribers15 November 2026 — 8,091 subscribers14 August 202615 November 2026
48 measurements spanning 93 days, net -6,921. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 7,053–16,051 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 48
Measured (UTC)SubscribersChange
15 Nov 2026, 15:078,091-434
9 Nov 2026, 22:468,525-221
6 Nov 2026, 03:498,746-124
2 Nov 2026, 23:298,870-157
31 Oct 2026, 05:399,027-487
28 Oct 2026, 04:519,514-413
25 Oct 2026, 02:509,927-169
24 Oct 2026, 02:1910,096-114
22 Oct 2026, 23:5410,210-170
21 Oct 2026, 21:2710,380-106
20 Oct 2026, 18:4810,486-152
19 Oct 2026, 20:1110,638-80
18 Oct 2026, 19:1710,718-89
17 Oct 2026, 17:0710,807-249
16 Oct 2026, 14:3911,056-38
15 Oct 2026, 15:5611,094-107
14 Oct 2026, 17:0111,201-147
13 Oct 2026, 08:2111,348-424
9 Oct 2026, 03:0211,772-379
4 Oct 2026, 15:5612,151first reading

Engagement

21 posts held, back to 1 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 60 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
1.97%
avg views ÷ 8,091 subscribers
Avg views / post
159
1 post measured
Reaction rate
—
this channel exposes no reaction counts
Posts in window
1
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.

What these figures were computed from
WindowRolling 30 days · latest post in window 28 October 2026
Posts held21 (1 July 2026 – 28 October 2026)
Views total159
Reactions total—
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken15 Nov 2026, 13:56 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.

Reaction mix

2 reactions across 2 posts, in 1 kind.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤2100.0%

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 2 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 2 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 1 July 2026 to 28 October 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: 1 of 1 post held from the last 30 days (100.0%) 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).

16 Oct 2026, 00:51 UTC288 viewsread 15 November 2026

机器人出入境已恢复 价格跟随市场涨价 @diguazhbot 要出敏感出入境的来找我人工出 价格稍微贵一点

8 Aug 2026, 20:04 UTC≈1,070 viewsread 15 November 2026

文全,补齐,猎魔 已跟随市场调价 已编辑

20 Jul 2026, 12:56 UTC≈1,820 views1 reactionsread 15 November 2026

寻找 需要文全/公网补齐/猎魔 量大代理客户 公网补齐 😀😃😀 排队秒 公网猎魔 😀😃😀 排队秒 可以排除 无视脱裤菜 保真不保漏 确认好再报 百分百的公网 全国文全 😀😃😀 排队秒 保真不保漏 集体户默认空会通知 要的话再出 报过的客户都说准 文全地址 😃😀 全天秒 非社工库出单 文全库出单 不是公网实时 报了不扯皮谢谢 然后永久用户名: @ran_hou

❤1

20 Jul 2026, 12:44 UTC≈1,350 viewsread 15 November 2026

@rennn 不再使用这个用户名 已被朋友高价收走 后面会重新购买新的用户名 现在用户名: @ran_hou 不要被骗了

12 Jul 2026, 17:55 UTC≈1,650 viewsread 15 November 2026

假地址机器人: @diguazhbot 代理量大老板可以来拿优势价格 😀😀一单 早七点半到晚七点半随时秒 需要的可以联系充值客服: @ran_hou 机器人频道: @ranhouyewu

8 Jul 2026, 15:18 UTC≈2,280 views1 reactionsread 15 November 2026

全网最全地区头: 11北京4️⃣🔤 12天津3️⃣🔤 13河北1️⃣🔤 31上海3️⃣🔤 32江苏1️⃣🔤 33浙江4️⃣🔤 34安徽4️⃣🔤 36江西4️⃣🔤 37山东3️⃣🔤 42湖北2️⃣🔤 43湖南1️⃣🔤 44广东4️⃣🔤 45广西1️⃣🔤 46海南1️⃣🔤 50重庆3️⃣🔤 52贵州3️⃣🔤 62甘肃4️⃣🔤 64宁夏1️⃣🔤 65新疆2️⃣🔤 地区户籍地: 11北京2️⃣🔤 31上海 2️⃣🔤 33浙江2️⃣🔤 34安徽 2️⃣🔤 43湖南 2️⃣🔤 44广东2️⃣🔤 50/51重庆2️⃣🔤 62甘肃 2️⃣🔤 地区头机器人: @ranhoudqt_bot 客服: @ran_hou 双向机器人: @ranhousxbot

❤1

5 Jul 2026, 23:55 UTC≈1,300 viewsread 15 November 2026

假地址 😀😀 早七点半到晚七点半 量大老板可以来拿优势价格 一直在秒 @ran_hou

1 Jul 2026, 08:41 UTC≈1,240 viewsread 15 November 2026

微支流水正常收单 微信流水不带ID /支付宝流水带ID 一月 🤩🤩🤩🤩 三月 🤩🤩🤩🤩 半年 🤩🤩🤩🤩 一年 🤩🤩🤩🤩 二年 🤩🤩🤩🤩 三年 🤩🤩🤩🤩🤩 回单:1~3个工作日 温馨提示:保真不保漏 ‼️ 不管出来多少条都按报单时间收费‼️

1 Jul 2026, 08:37 UTC767 viewsread 15 November 2026
File

强登12306 出行记录 🤩🤩🤩 报单提供 大头 @ran_hou

1 Jul 2026, 08:33 UTC652 viewsread 15 November 2026

交管12123名下车 🤩🤩🤩 报单;名字 身份证 不需大头

Showing the 12 most recent of 21 posts we hold for @ranhoupingdao. 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 edited after publishing

@ranhoupingdao edited 2 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.

First edit seen
19 August 2026
Most recent edit
3 November 2026

Mentions

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.

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 15 November 2026 — this entry's latest reading, not the date you are reading this.

“然后业务频道” (@ranhoupingdao), 8,091 subscribers as measured 15 November 2026. Telegram Register, tgregister.com/channel/ranhoupingdao.

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.