===== 评论区 ===== b bi: @jogle_channel_bot妞好看吗,有微信吗? b bi: 我看美团25年后就没人评论了 G G: (➤b bi) 这家店身处闹市 有点危险
❤7👍1
Channel
@olddriver_subbb
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
33,780subscribers
+101 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 31,623–100,000.
| Telegram ID | -1001944679344 |
|---|---|
| Type | Channel |
| Username | @olddriver_subbb |
| Description | 群主 @olddriver_sub 找我上榜 @szgod_bot 苏州公榜群 https://t.me/olddriver_szb 我是专属机器人🤖 旗下: 参考 公榜 评价 足浴 色色 五大频道,投稿|投诉提交:时间 地点位置人物 TG号 TG名称 店家商户名 ,消费记录 (账单 导航记录 聊天 支付任意一作为参考) 起因 经过 结果 抓住重点经过简单描述, 我收到会第一时间回复你。感谢信任 愿您我真诚到永远 |
| Created | Between 1 April 2023 and 31 October 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 29 September 2026 |
| Measurements held | 33 |
| Confirmed unchanged | 1 time, most recently 29 September 2026 |
| On Telegram | t.me/olddriver_subbb |
Adult — 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 9 September 2026 and assigned it the closest of 31 fixed categories, at 68% 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 |
|---|---|---|
| 29 Sept 2026, 13:20 | 33,780 | -73 |
| 17 Sept 2026, 20:38 | 33,853 | +13 |
| 15 Sept 2026, 20:17 | 33,840 | +22 |
| 14 Sept 2026, 02:16 | 33,818 | +7 |
| 12 Sept 2026, 06:41 | 33,811 | +6 |
| 10 Sept 2026, 04:17 | 33,805 | +129 |
| 6 Sept 2026, 18:58 | 33,676 | -16 |
| 4 Sept 2026, 10:15 | 33,692 | -2 |
| 3 Sept 2026, 00:54 | 33,694 | +10 |
| 1 Sept 2026, 22:38 | 33,684 | +10 |
| 31 Aug 2026, 21:12 | 33,674 | -6 |
| 30 Aug 2026, 20:57 | 33,680 | +9 |
| 29 Aug 2026, 20:37 | 33,671 | -4 |
| 28 Aug 2026, 17:04 | 33,675 | +6 |
| 27 Aug 2026, 13:33 | 33,669 | +4 |
| 26 Aug 2026, 10:16 | 33,665 | -1 |
| 25 Aug 2026, 11:42 | 33,666 | -6 |
| 24 Aug 2026, 14:15 | 33,672 | -18 |
| 22 Aug 2026, 21:08 | 33,690 | +24 |
| 21 Aug 2026, 10:04 | 33,666 | first reading |
52 posts held, back to 23 June 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 91 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.
| Window | Rolling 30 days · latest post in window 10 September 2026 |
|---|---|
| Posts held | 52 (23 June 2026 – 10 September 2026) |
| Views total | 150,850 |
| Reactions total | 291 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 30 Sept 2026, 07:23 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.
Lifetime counters from Telegram’s own channel header, read 30 September 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.
716 reactions across 46 posts, in 13 distinct kinds. The most used accounts for 30.3% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 217 | 30.3% | |
| 😱 | 157 | 21.9% | |
| 🤡 | 97 | 13.5% | |
| 👍 | 80 | 11.2% | |
| 🤬 | 34 | 4.75% | |
| 😁 | 31 | 4.33% | |
| 👎 | 28 | 3.91% | |
| 🖕 | 28 | 3.91% | |
| 🤣 | 16 | 2.23% | |
| 🔥 | 13 | 1.82% | |
| 🎉 | 8 | 1.12% | |
| 🤮 | 6 | 0.838% | |
| 💯 | 1 | 0.14% |
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 51 of the 52 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 716 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 52 most recent posts we hold, published 23 June 2026 to 10 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.
===== 评论区 ===== b bi: @jogle_channel_bot妞好看吗,有微信吗? b bi: 我看美团25年后就没人评论了 G G: (➤b bi) 这家店身处闹市 有点危险
❤7👍1
#无锡市 #梁溪区 #红豆人民路9号 # 370元 95 BT 半套 中项 口爆 毒🐉 #店名简悦 (美团 高德地图都能搜到)
❤4
===== 评论区 ===== 骚包张奶子: 有幸去过,丑的一比,完全没有身材可言,皮肤很黑也不光滑服务也很潦草, 白桃: 在忙的时候也不上tg,没有及时回复你确实对不起。没有鸽你,没有给准确的位置,就没有约成功。 檀木: 那你可以什么呢?找个像样的借口不行吗 Shi Jordan Ⅱ: (➤白桃) 哎呦,当事人出来了,可以就是可以,不可以就是不可以,臭逼自己不会合理安排,浪费别人时间,找什么借口 Shi Jordan Ⅱ: (➤AAAAAA 五a笔刷) 龟男滚,你帮他说话也不会有免费臭逼草的 Shi Jordan Ⅱ: (➤AAAAAA 五a笔刷) 论你妈逼,你这个乌龟竟然还长膝盖,那么爱下跪。从来没有什么报地址才算约成功的规矩,报地址是妓女的义务,不报就是她的问题,从来只有收钱的迁就付钱的,付钱的迁就收钱的算什么道理? 叶落葬红尘: 我去感觉还可以,挺不错的 要吃鱿鱼吗: (➤骚包张奶子) 见人下菜典型,黑 没什么服…
❤6
#被鸽子🕊️ #14点57分到15点15分 明确确认约的19点,17点04分到18点13分追问地址,被告知约满了 #提前约好时间,一直不发地址,距离约好的时间不到一小时,突然说约满了,直接把我鸽了 #白桃 @baitaoszly
❤1
===== 评论区 ===== shuai: 厉害 霸王 🦍: 防内射保证金😂 We Ew: 苏州也有我刚被骗,一个叫西米的,处男破处还要有保证金 Calandra Kobler: 张家港有没有靠谱的店呢? 恢恢: 人都没见到就付钱啊,你记住个人的见面付钱,去店里的玩完付钱
😁5❤1
@GOGOBMW456 #避坑 #避雷 #鸡头群 #被骗188元定金 #投稿避雷张家港修车大队这个组所有的人,这个群全是骗子,全是被骗🐔头在聊天,没有女的真人,各种手段骗你交定金,开门前还要收费,这个组创立到现在全是骗子。前两天在另一个群里看一个兄弟同样被骗我的人又被骗了,发出来让大家避雷一下,最好大家能把这个组举报了
👍17❤5🤡2😁2
#星健中心4号楼206室 #徐阳花园13幢1503室 办事单位 : 苏锦派出所 澄阳派出所 共计三位电报老师 三位狼友 , #苗苗 #卡戴珊 #陈音音 六月被抓记录 芙儿 洛儿
😱97❤8👍4👎4😁4
#理理 #去过的佐证
❤4
#理理 @lilideaixin123 这个逼在尹山湖Yangosoho公寓11楼开课,奶子下垂严重,胸前跟挂了两坨肉一样,还没老妈子的胸有弹性,床上机车,干了没两下就说腿麻了,而且唉声叹气很不耐烦,花了钱还要哄着她,很影响心情,后面套子上油蹭完了当她面把套子取下来的,她也知情的,说没有套子,又把那个套子撑开给我戴上,结果跟去过的人说我拔套,她才对我态度不好,我就想说你妈死了,老子刚插上有五分钟吗,就这疼那疼的,我要拔套了她后面还让我接着干吗?信的人也是傻逼,你妈说啥你信啥 你不给我就走了啊,没蛇没69,谁要原价玩你啊 还跟别人说我最后强行要的优惠 不是我跟你商量好的,给了你钱开始做的? 我报告写的哪一条是我造谣? 你奶子没下垂? 奶子下垂严重,胸前跟挂了两坨肉一样,还没老妈子的胸有弹性,床上机车,干了没两下就说腿麻了,而且唉声叹气很不耐烦,花了钱还要哄着她,很影响心情,后面套子上油蹭完了当她面把套子取下来的,她也知…
❤18👍3
#小倩 #体验过的佐证
❤3
#便宜没好货 #机车 口👄J8不到五秒 #进门出门五分钟,时间媲美站街快餐 #不给换姿势,一个姿势到结束 #小🐔懒不洗澡,编借口找理由物业停水 #我是看群里有人说,他4张优惠一张,想着便宜卸个火,再差能差到哪去。结果进去黑灯没开,直接脱了我的衣服,收了我的钱,然后口了不到5秒钟,就要戴套。我说怎么不洗澡?他说停水了。然后让我站在床边插了几分钟,就结束了。真的进出五分钟。真的是便宜没好货。 #小倩 @zcy8100 #中翔丽晶公寓 27楼
❤8
#歪歪 #代聊回复的很官方 #体验过得佐证
🤮6❤2
Showing the 12 most recent of 52 posts we hold for @olddriver_subbb. 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.
@olddriver_subbb edited 3 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.
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.
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.
@olddriver_subbb 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.
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 29 September 2026 — this entry's latest reading, not the date you are reading this.
“苏州参考馆” (@olddriver_subbb), 33,780 subscribers as measured 29 September 2026. Telegram Register, tgregister.com/channel/olddriver_subbb.
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.