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Channel

苏苏的朋友圈

@uhnbgdfd

On this record: Growth · Engagement · What this channel posts · Posts · Citations · Cite this entry

495subscribers

-93 since we began measuring on 6 September 2026

Risers and fallers across the register · movement among entries of Under 1,000.

Register entry

Telegram ID-1002406919643
TypeChannel
Username@uhnbgdfd
CreatedBetween 1 September 2024 and 31 March 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 September 2026
Last confirmed live17 September 2026
Measurements held4
Confirmed unchanged1 time, most recently 17 September 2026
On Telegramt.me/uhnbgdfd

Growth

495588541.56 September 2026 — 588 subscribers6 September 2026 — 588 subscribers9 September 2026 — 584 subscribers17 September 2026 — 495 subscribers6 September 202617 September 2026
4 measurements spanning 11 days, net -93. 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 481–602 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
17 Sept 2026, 15:41495-89
9 Sept 2026, 10:56584-4
6 Sept 2026, 13:22588no change
6 Sept 2026, 08:47588first reading

Engagement

18 posts held, back to 12 March 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 page of Telegram’s post history, 20 posts per page.

ERR · 30 days
0.808%
avg views ÷ 495 subscribers
Avg views / post
4.0
2 posts measured
Reaction rate
this channel exposes no reaction counts
Posts in window
2
of 18 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 5 September 2026
Posts held18 (12 March 20265 September 2026)
Views total8
Reactions total
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken6 Sept 2026, 13:22 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

Video runtime
3s
Average length
3s

Measured directly from 1 video 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.

Recent posts

30 Aug 2026, 12:00 UTC6 viewsread 6 September 2026
Forwarded from @SHDD333

💃老师:#苏苏 🤖链接:https://t.me/shanghaidadao/11914 💒位置:#浦东 ------------------ 💌出击报告:文采一般简单描述!嫩妹极品,三点粉嫩,熊大手感好,bb水多粉嫩,有初恋的感觉,全程非常配合让我非常满意,喜欢嫩妹的冲!

17 Aug 2026, 09:16 UTC9 viewsread 6 September 2026
Forwarded from @SHDD333

💃老师:#苏苏 🤖链接: https://t.me/shanghaidadao/11417 💒位置:#浦东 ------------------ 💌出击报告:一进门,老师主动打招呼,递水拿鞋,豪不冷场,看了一眼,真人比照片好看啊,是我喜欢的类型,女友感十足,身材性感,皮肤白皙,服务起来毫不含糊,口活很好,一顿口的我提枪上阵,老师下面不是一般的湿,包裹感满满,抱着老师就好像抱着女友一样,老师在耳边轻轻的呻吟声恰到好处的刺激我,全力输出,交货.休息期间和老师沟通愉快,还和老师女友一样抱了抱.第二发,老师随着我的力度,从女友感变的骚气十足,哈哈,非常给力,让我感觉自己好像真的越来越厉害一样!体验感满分!

10 Aug 2026, 02:37 UTC17 viewsread 6 September 2026
Forwarded from @SHDD333

💃老师:#苏苏 🤖链接: https://t.me/shanghaidadao/11417 💒位置:#浦东 ------------------ 💌出击报告:下午临时有空,约了个pp想体验一下喷泉,按时到地方,跟着ls的指引来到课室,简单聊了一会,就交水费一起去洗澡了,过程全自动,正式环节就不细说了,主要是被秒了,也看到了喷水,cj目的达成

6 Aug 2026, 07:30 UTC18 viewsread 6 September 2026
Forwarded from @SHDD333

💃老师:#苏苏 🤖链接: https://t.me/shanghaidadao/10390 💒位置: #浦东 ------------------ 💌出击报告: 一个月未见,甚是想念,再加上此女天天在频道上面发一些诱惑视频啊,图片啥的,弄得我是心里痒痒的,果断是周一打个招呼,周二晚上约上,本来下午4点的,本来有点失落,然而万万没想到居然还能有个鸽子位,我定然选择果断出击,已经出击过三次也就不会有什么负责流程了。内心满是激动自然也就没了忐忑。 进到房间,熟悉的环境,熟悉的人吗,热情的拥抱,让人陶醉的体香,由于约的是PP时间足够,先上在沙发上面寒暄叙旧,渐入佳境之时,我们双方都帮对方脱掉衣服,两两牵手至浴室一起共浴,挺挺的大白兔,一只手根本握不住,浴室一阵调情,洗了一下残废澡,双方情绪自然也是到达顶点,迫不及待的来到老师的卧室, 此时老师化身小猫咪,又是亲胸又是吞肉棒,口活一会之后,妹子有点发骚受不了,直接给我戴上小雨伞,化身骑士策

2 Aug 2026, 14:25 UTC14 viewsread 6 September 2026
Forwarded from @SHDD333

💃老师:#苏苏 🤖链接: https://t.me/shanghaidadao/11417 💒位置: #浦东 ------------------ 💌出击报告:关注苏苏老师很久了,之前是工作太忙了,就一直没有约,等到我有空了后续老师又去深圳开课了。这段时间看到苏苏老师回来上海开课了,果断预约了一个pp!见到老师的第一眼就觉得来对了,这妹子好高,御姐范儿。让人好有征服的欲望,想到等一下就跟她啪啪啪,老二已经硬的不行啦。老师很热情,温柔。在床上柔韧性很好,各种姿势都能轻松拿捏,水多,狠狠地征服,她嘴里一直喊着“老公,快操死我呀,射给我!”。太得劲儿了,敏感体质,很容易高潮的那种!后入看着她的大屁股,很有弹性,啪啪的撞击声,很带劲!细节把握的很好,没有那种很刻意去叫的那种感觉,都是很自然的呻吟,很满意的一次出击,有空了必返!!

31 Jul 2026, 08:21 UTC12 viewsread 6 September 2026
Forwarded from @SHDD333

💃老师:#苏苏 🤖链接: https://t.me/shanghaidadao/11417 💒位置: #浦东 ------------------ 💌出击报告:声音超级嗲,一开口就带着软软的鼻音,光是说话就能把人听硬。她主动得很,进门后没怎么客气,直接上手做指滑,手指灵活地探进去打圈、抽送,水声很快就响起来。边做边用那种嗲声问“舒服吗”,又骚又甜。口的部分她也很投入,含住后吸吮有力,时而深吞时而用舌尖挑弄。欲望之花被她演绎得很到位,身体完全打开,主动把最敏感的地方送过来,配合度极高。真正进入后各种趴姿她都肯配合,想后入就后入,想压低一点她就自己把腰塌下去,声音一直嗲着叫,又软又密。主动热情到几乎不用引导,整场都被她的声音和动作带着走。嗲声、指滑的准、口的投入、再加上各种趴姿的高配合,体验又色又有记忆点。结束时她还用那种软软的声音问还要不要,完全是主动型。

11 Jul 2026, 10:40 UTC24 viewsread 6 September 2026
Forwarded from @SHDD333

💃老师:#苏苏 🤖链接:https://t.me/shanghaidadao/10390 💒位置: #浦东 ------------------ 💌出击报告:风骚性感又带纯欲天花板的身材,奶子又大又软,腰细得一手能握,屁股又圆又翘,皮肤白嫩,脸蛋甜美中透着勾人的骚劲儿。她声音超级嗲,一口一个“哥哥~要我嘛”,听得人骨头都酥了。服务全程各种趴趴姿势让你直接着迷!先是经典后入,她跪在床上高高翘起大屁股,我从后面插进去,那又紧又热的逼死死夹着我,一缩一缩吸得特别舒服。她一边被操一边扭腰迎合,屁股肉浪一波一波,嗲声嗲气地叫:“哥哥操深一点……苏苏好痒……啊~”我把她压成各种姿势猛干,她都配合得特别好,腿抬得高高的,腰往下塌,屁股翘得老高,纯欲又风骚的样子直接把我干上头。操着操着她还主动摇臀夹我,里面又湿又热,吸力惊人。苏苏渴望被爱的样子太犯规了,叫床声音又甜又嗲,骚话连篇,身体又软又会扭,简直是纯欲和风骚的完美结合。各种趴趴姿势玩得我腿

10 Jul 2026, 11:16 UTC22 viewsread 6 September 2026
Forwarded from @SHDD333

💃老师:#苏苏 🤖链接:https://t.me/shanghaidadao/10390 💒位置:#浦东 ------------------ 💌出击报告:真是欲望之花!脸蛋甜美,身材火辣,前凸后翘,皮肤嫩滑,尤其是那双会说话的大眼睛,一看就很骚。她主动热情到爆,一见面就抱着我舌吻,舌头又软又灵活,深深缠着我狂吸口水,吻得我差点喘不过气,口水交换得特别色情。上床后直接69,她主动骑脸,小逼又粉又多水,坐在我嘴上疯狂磨,我舔得她浪叫连连,她也低头给我口活,深喉猛吸,技术一流,喉咙收缩夹得特别紧。玩着玩着她还给我指滑,涂了润滑液用手指灵活地撸我鸡巴和按摩蛋蛋,配合舌头一起伺候,爽得我头皮发麻。苏苏全程超级主动,欲望之花名不虚传,各种姿势都积极配合,叫床又甜又浪,服务态度满分,没有一丝敷衍。舌吻、69和口活质量都很高,热情得像要把我榨干一样。

Showing the 12 most recent of 18 posts we hold for @uhnbgdfd. 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.

Forward network

Republishes

Channels on the register whose posts this channel has forwarded.

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 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.

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 17 September 2026 — this entry's latest reading, not the date you are reading this.

“苏苏的朋友圈” (@uhnbgdfd), 495 subscribers as measured 17 September 2026. Telegram Register, tgregister.com/channel/uhnbgdfd.

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.