Telegram RegisterThe public register of Telegram
Telegram profile photo for 💕广深🦋蜂腰肥臀巨乳卡戴珊泡泡朋友圈🍀

Channel

💕广深🦋蜂腰肥臀巨乳卡戴珊泡泡朋友圈🍀

@paopao201819

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

6,152subscribers

+83 since we began measuring on 7 August 2026

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

Register entry

Telegram ID-1002250930237
TypeChannel
Username@paopao201819
Description私聊: @paopao769 泡泡资料 照片 福利❤️ 💓⬇️ 原频道2w 没了 备用频道 主频道 https://t.me/+b2GlUwFJ6G8yY2Q1 机器人 @paopao769_bot
CreatedBetween 1 October 2024 and 31 March 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live4 November 2026
Measurements held21
Confirmed unchanged1 time, most recently 4 November 2026
On Telegramt.me/paopao201819

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 12 September 2026 and assigned it the closest of 31 fixed categories, at 76% 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

6,0466,1526,0997 August 2026 — 6,069 subscribers8 August 2026 — 6,083 subscribers11 August 2026 — 6,128 subscribers15 August 2026 — 6,139 subscribers17 August 2026 — 6,136 subscribers20 August 2026 — 6,046 subscribers24 August 2026 — 6,050 subscribers30 August 2026 — 6,053 subscribers2 September 2026 — 6,065 subscribers6 September 2026 — 6,069 subscribers11 September 2026 — 6,087 subscribers15 September 2026 — 6,078 subscribers27 September 2026 — 6,085 subscribers5 October 2026 — 6,097 subscribers11 October 2026 — 6,121 subscribers14 October 2026 — 6,138 subscribers20 October 2026 — 6,145 subscribers23 October 2026 — 6,140 subscribers26 October 2026 — 6,145 subscribers29 October 2026 — 6,146 subscribers4 November 2026 — 6,152 subscribers7 August 20264 November 2026
21 measurements spanning 89 days, net +83. 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 6,030–6,168 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 21
Measured (UTC)SubscribersChange
4 Nov 2026, 09:106,152+6
29 Oct 2026, 16:106,146+1
26 Oct 2026, 19:566,145+5
23 Oct 2026, 09:456,140-5
20 Oct 2026, 09:156,145+7
14 Oct 2026, 18:106,138+17
11 Oct 2026, 14:566,121+24
5 Oct 2026, 12:566,097+12
27 Sept 2026, 06:026,085+7
15 Sept 2026, 08:406,078-9
11 Sept 2026, 13:226,087+18
6 Sept 2026, 15:396,069+4
2 Sept 2026, 00:176,065+12
30 Aug 2026, 04:556,053+3
24 Aug 2026, 09:346,050+4
20 Aug 2026, 11:126,046-90
17 Aug 2026, 20:176,136-3
15 Aug 2026, 00:046,139+11
11 Aug 2026, 17:376,128+45
8 Aug 2026, 09:046,083first reading

Engagement

44 posts held, back to 26 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 13 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
45.5%
avg views ÷ 6,152 subscribers
Avg views / post
2,800
4 posts measured
Reaction rate
0.121%
reactions ÷ views · ER floor
Posts in window
4
of 44 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.

What these figures were computed from
WindowRolling 30 days · latest post in window 17 October 2026
Posts held44 (26 July 2026 – 17 October 2026)
Views total11,200
Reactions total10
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken6 Nov 2026, 16:53 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
50
Videos
33
Links
73

Lifetime counters from Telegram’s own channel header, read 6 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.

Video runtime
1m 47s
Average length
15s

Measured directly from 7 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

94 reactions across 28 posts, in 3 distinct kinds. The most used accounts for 90.4% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤8590.4%
👍77.45%
🍾22.13%

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 33 of the 44 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 94 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 44 most recent posts we hold, published 26 July 2026 to 17 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: 0 of 4 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).

17 Oct 2026, 03:29 UTC≈2,610 views6 reactionsread 6 November 2026
Photo

第三站7.8,卡戴珊泡泡 @paopao769 能约上也是我的幸运😮‍💨😮‍💨很活泼是泡泡 一个多月前就注意到泡泡了,一个月前约了听信了别人的评价,害得我真的后悔。这次看见泡泡开课了早早就约好了也刚好遇见我生日,过来的时候提前半个小时到了,泡泡说上一个客人还没走完在楼下逛了一下看见一个水果店刚进了货赶着新鲜就买了几盒然后在楼下等了十几分钟,泡泡就告诉我怎么上去,哈哈死退快跑加速上楼,泡泡留门开门进去,见到到泡泡,泡泡颜值真的漂亮心目中排第一,进门以后跟泡泡说给她带了水果,泡泡还给我点了奶茶真的很贴心,然后我跟泡泡说刚好今天生日,然后泡泡还泡去点了蛋糕(被感动到😭),聊了一会天拉着泡泡去洗澡,嘿嘿泡泡还穿着黑丝帮我洗澡,还用那对大灯蹭我后背真的舒服,洗完澡还有水中萧,螺旋深喉真的很到位好几天没要了,差点被泡泡口射了,然后洗完澡泡泡还帮我擦干身体,带我去阳台选情趣服,太调皮了我说要白色的衬衫,她拿了一件黑色说,黑色也好看真的爱了,…

❤6

11 Oct 2026, 06:06 UTC≈2,990 views3 reactionsread 6 November 2026
Photo

😀#天河 #泡泡 【广州学院】: @gzwww @gzbbb 【上课日期】:10月10日 【上课费用】:#包时/3500 【报告来源】:#月初 @Qiyuechui 【体验细节】: 这是个充满坎坷的cj,从上个月一开始我就已经约好了,奈何天不遂人愿,静静地等了一个月,泡泡终于回来广州开了,也是没有丝毫耽误直接约上,临近出发,我心里扑腾扑腾的仿佛是我第一次cj一样怎么都静不下来,我不知道怎么了,总觉得她会给我不一样的感觉,哎真是大塞车一个小时才来到楼下,按着指引上去找到房间号来到门前,我站在门口做了会心里准备,轻轻的敲两下门,门开打开的一刹那,其实我已经有点手足无措了,这颜值,这身材,还有身上散发的阵阵香水味,我已经被泡泡的眼神给勾走了,来到沙发坐下,啥都不说先抽根烟,她给我递过来一根我们边抽边聊,交上课费,泡泡拉着我就来到镜子脸上,我第一时间其实还没反应过来,来到镜子前,我看着她那漂亮又有个俏皮劲的脸,她让我摸她,一抓摸向奶子,…

❤3

10 Oct 2026, 08:25 UTC≈2,660 views1 reactionsread 6 November 2026
Photo

😀#天河 #卡戴珊泡泡 【广州学院】: @gzwww @gzbbb 【上课日期】:10月9日 【上课费用】:#包夜/5888 【报告来源】:#毛毛 @maomao_370 【体验细节】: 秋天,夹杂在激情的夏日与刺骨的寒冬之间,即是过渡,也是漂泊空虚之时。 自从上次找泡泡度过一天后,短时间对其他人失去了任何兴致,于是我相信自己的感觉,出击以来上过的夜课给我的体验都是无比糟糕,于是便有了想与泡泡度过今宵的想法。 到了既定时间,按照她的指示上楼,进门后映入眼帘的,是性感妩媚,带有一丝害羞可爱(以及一点痞帅)的泡泡,依旧穿着无法盖住她那蜂腰、肥臀、巨乳的连衣裙 这个科室比上次多了很多大镜子,足够能让泡泡在爱爱时尽显她的魅力。 询问泡泡今天累不累,她不语,拖我到镜子面前,一把抱住了我,她的体温、香水(自己调的)、犯规的身材还有那含情脉脉的双眼我尽收眼底,忍不住开始上下起手,我们也情不自禁的相吻,交换唾液,不知过了多久。没有着急马上开始,…

❤1

9 Oct 2026, 07:07 UTC≈2,940 viewsread 6 November 2026

#芳华报告 老师名字: #卡戴珊泡泡 学生留名: # 零贰 联系方式: @paopao769 时间: 10.8 地址:广州天河 价格:2800 2小时包时 上课过程:一直盯着泡泡的频道,她有可爱的脸蛋却有反差的曼妙身姿,是我很很很喜欢的类型。脸很漫画精致妆容 身材也是漫画身材!有胸屁股还有腰! 没有一丝赘肉!天赋怪 偶然看到泡泡要来广州开课,听说一直很满,所以蹲了很久才有幸抢到一个包时。 到了晚上,带着期待与紧张的心情与泡泡会面,一开始还走错了门,但最终还是成功见到了泡泡,一进门我就看到躲在门后的泡泡,当时她还穿着黑色长衣看不清身材,但脸蛋和频道上的没差,甚至真人比频道上加了滤镜的图片更好看! 于是立马交了水费,准备深入交流。看到我比较紧张,泡泡就示意我到镜子旁摸摸她的胸和屁股,好大好软呀,随后她慢慢脱下衣服我也看到了藏在衣服下的魔鬼身材,于是和泡泡紧紧相拥,身上香喷喷的都舍不得放开了。摸了一会后她说看我硬了就说先…

7 Oct 2026, 05:14 UTC≈1,940 views1 reactionsread 6 November 2026
Video

🐸🐸🐸😘😘哈喽哈喽,❤️8号广州开一个星期国庆快乐啊啊啊啊啊啊😤😤😤 今天开始排课! 你来! 不来泡泡你是小傻瓜你来!之前留定的优先❤️ ggogogogo

🍾1

22 Sept 2026, 11:45 UTC≈4,860 views7 reactionsread 6 November 2026

还在休息🀄️❤️ 啊啊啊啊啊啊~

❤7

16 Sept 2026, 10:31 UTC≈5,310 views2 reactionsread 6 November 2026

出击报告: { telegram.me/+pdO6uCN5l81iNmY1 } 学生验证留名:放纵 验证时间:9月15日 老师昵称:#卡戴珊泡泡 老师联系方式: @paopao769 地市坐标:深圳 上课花费:5888 出击体验:这一次的相遇,更像是一场热恋,见到泡泡后,在她的建议下,紧张刺激的去水会体验了第一次,两个菜鸡还要打会台球和乒乓球,结果在尴尬中匆匆离场,之后来到一条小吃街,她就像个小姑娘一样开心的看着各种小摊,挑选了几样小吃后在一家苍蝇馆子吃起了麻辣烫(苍蝇馆子真的有苍蝇),这一晚我们是幸运的,因为这是店家的最后一份了,之后回到泡泡的住所,即使她已经很累了还是极力的配合了一次,在沙发上聊了一会就睡去了,早上起来,跟半醒状态的睡美人来了一次后就离开了,结束了这平淡无奇的一晚,正如她所说希望是女友而不是毫无意义的上课,泡泡给我的感觉真的就如女友一样,让我重回了热恋时期 优点缺点:想不到有啥缺点,都是优点 评分标准:…

❤2

16 Sept 2026, 08:05 UTC≈2,240 views2 reactionsread 6 November 2026
Photo

啊啊啊啊啊啊 休息了 来例假了约了的下次例假结束优先排课 抱歉❤️ 下次见❤️ 好泡不怕晚 短暂的分别为了更好地相遇❤️

❤2

14 Sept 2026, 17:18 UTC≈3,730 views1 reactionsread 6 November 2026

集团每日五折工兵劵,更多现金大奖期待您的参与 深圳集团狼友交流群组:https://t.me/+T_cG2VyxBB8xYzU1 深圳集团老师公开榜: https://t.me/ShenZhen_68 深圳集团老师广告群: https://t.me/Shenzokba 深圳集团老师报告参考: https://t.me/yeshanghai96 ‼️📢投诉上榜建议: @bbca12

❤1

10 Sept 2026, 17:57 UTC≈3,480 views3 reactionsread 6 November 2026
Photo

😀#天河 #泡泡 【广州学院】: @gzwww @gzbbb 【上课日期】:9月10日 【上课费用】:#下午茶/3388 【报告来源】:#不小心打开的潘多拉魔盒 @zhuang9090 【体验细节】: 一个月前刚刚下载tg的时候就有人推荐泡泡,当时也是泡泡的广州首开,我一看又御又萝,还自评卡戴珊,我就喜欢这种,刚欲联系上课时发现已经没有空位了,无奈只能约下一次广州之行,本来说是红休完就来广州,苦苦等待红休结束,以为泡泡终于要来了,还提前定了夜课,结果贪玩泡又休息了十几天,原定的夜课也因为时间冲突,只能改约下午茶了,转眼到达出击日,泡泡说被桩了不中了要休息了,厚礼蟹,我超威,瞬间感觉天要塌了,我都要哭了,苦苦等待一个月近在眼前的泡泡就要飞了,感觉天空一片黑暗。在难过到极点的时候,叮咚,收到了泡泡的消息,说我约了好久了,她不忍心鸽我,她忍一下照常上,(敬业,太tm敬业了,我哭死) 。于是乎我带着忐忑的心情来到指定地点,来早了,楼下溜…

❤3

Showing the 12 most recent of 44 posts we hold for @paopao201819. 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

@paopao201819 edited 1 post 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
8 August 2026
Most recent edit
10 August 2026

Forward network

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 3 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.

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

“💕广深🦋蜂腰肥臀巨乳卡戴珊泡泡朋友圈🍀” (@paopao201819), 6,152 subscribers as measured 4 November 2026. Telegram Register, tgregister.com/channel/paopao201819.

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.