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Channel

妮妮秘密基地😇

@xiaogushinini

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

1,367subscribers

+102 since we began measuring on 31 August 2026

Risers and fallers across the register · movement among entries of 1,000–3,162.

Register entry

Telegram ID-1003752933327
TypeChannel
Username@xiaogushinini
CreatedBetween 1 February 2026 and 24 May 2026 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded31 August 2026
Last confirmed live18 September 2026
Measurements held6
Confirmed unchanged1 time, most recently 18 September 2026
On Telegramt.me/xiaogushinini

Topic

Education — 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 17 September 2026 and assigned it the closest of 31 fixed categories, at 67% 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.

Growth

1,2651,3771,32131 August 2026 — 1,265 subscribers31 August 2026 — 1,277 subscribers5 September 2026 — 1,323 subscribers10 September 2026 — 1,369 subscribers14 September 2026 — 1,377 subscribers18 September 2026 — 1,367 subscribers1,36731 August 202618 September 2026
6 measurements spanning 18 days, net +102. 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 1,248–1,394 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
18 Sept 2026, 03:161,367-10
14 Sept 2026, 03:181,377+8
10 Sept 2026, 12:591,369+46
5 Sept 2026, 00:411,323+46
31 Aug 2026, 23:381,277+12
31 Aug 2026, 03:151,265first reading

Engagement

20 posts held, back to 24 May 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
21.9%
avg views ÷ 1,367 subscribers
Avg views / post
300
1 post measured
Reaction rate
this channel exposes no reaction counts
Posts in window
1
of 20 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 30 August 2026
Posts held20 (24 May 202630 August 2026)
Views total300
Reactions total
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken31 Aug 2026, 03:15 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
34s
Average length
7s

Measured directly from 5 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

18 reactions across 10 posts, in 1 kind.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
18100.0%

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 14 of the 20 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 18 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 20 most recent posts we hold, published 24 May 2026 to 30 August 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

9 Aug 2026, 11:44 UTC≈1,840 views0 reactionsread 31 August 2026

【出击日期】:8.8 【妹子花名】:妮妮@nini9986 【环境卫生】:居家,很温馨 【修车水费】:1400 【所在位置】:xishan区 【颜值相似】:9 【胸器罩杯】:B 【服务项目】:莞式服务 【机车行为】:无 【优点缺点】:很好看 【推荐程度】:10 【综合短评】:老师很热情,。会所级别的服务,先是b面,全身过水漫游,最牛逼的就是口痧,一口整个后背不喘气的,就连腿都做了过水漫游,进入最喜欢的环节,毒,龙,真的是纯👅,结束a面,还是指划胸划,我怕痒,直接进入口活环节,!深喉牛的一逼,把持不住带上雨伞老师上,几分钟结束战斗,很好的一次体验

8 Aug 2026, 06:34 UTC≈1,870 viewsread 31 August 2026
Video

不露点真材实料❗️你都不知道我叫妮妮😏

6 Aug 2026, 07:08 UTC≈1,980 views2 reactionsread 31 August 2026
Photo

被夸奖是件很幸福的事❤️

2

5 Aug 2026, 07:29 UTC≈1,880 views2 reactionsread 31 August 2026
Forwarded from @wuxilaosijibaogaoPhoto

【时间】:2026-08-01 【老师】:妮妮 【留名】:猴哥 【人照】:9 【颜值】:9 【身材】:10 【服务】:10 【态度】:10 【环境】:10 【综合】:9.67 【过程】:久违的护士小妮妮回来了,上次约她,约好时间准备出发,结果临时来姨妈,成为了我的遗憾,这场刷到上线,立马出击,停车方便,教室干净,一次性用品都有,进门交了水费,就突然把妮妮按在床上🐍,我本人有点癖好,痴迷于强奸剧情,由于跟妹妹提前沟通过,所以妮妮配合的非常到位,🐍的我非常上头,弟弟都要爆出来了,差点没忍住提枪上马,好在妹妹提醒我,没洗澡,没戴套不可以哦,随即冷静下来,去洗澡,妮妮非常爱干净,给我下面洗的非常干净,我调戏她之前是不是在男科干过哈哈哈,上床便是基础的服务了,毒龙我不喜欢就没让做,抱着妹妹一直🐍,来感觉了就上套,开干,全程我主动带节奏,没有按照传统出击流程,妹妹也是非常配合,满足我的所有性癖,此次出击,更像是许久未见的情人会面,那种感觉,

2

5 Aug 2026, 04:54 UTC≈1,720 views1 reactionsread 31 August 2026
Photo

开课啦❤️今天好响的雷❤️

1

2 Aug 2026, 00:54 UTC≈2,550 views1 reactionsread 31 August 2026

#无锡老司机 报告模版 【验证留名】 :说好的幸福呢 【验证时间】:2026-8-1 【妹子花名】:小护士妮妮 【联系方式】tg: @nini9986 【联系问题】:电报 【所在位置】:无锡 【修车水费】:700 【身高身材】:165 【颜值相似】:9 【凶器罩杯】:c 【服务内容】:ab面,毒龙,口,做 【服务详情】:从来没写过报告,今天体验过后意犹未尽,忍不住还是想给兄弟们推荐一下,妮妮老师夯暴了,进门就惊艳到我了,好漂亮啊!像哪个女明星想不起来了,衣品也很好,气质容貌俱佳!交完水费之后老师全程帮洗,去床上做ab面,过程中指滑、毒龙、舔蛋蛋、课表服务一个不少,老师的舌头好软好滑,差点给我口出来。戴上tt,先是女上,然后传教士、后入,最后再换传教士出货,过程中看着老师美美的脸蛋,忍不住次次都深插到底。 总之,老师真的好美,服务也是棒棒的,过两天必定二刷 【机车行为】:无 【优点缺点】:老师非常温柔配合 【推荐程度】:五颗

1

1 Aug 2026, 09:52 UTC≈2,400 views0 reactionsread 31 August 2026
Photo

【时间】:2026-08-01 【老师】:妮妮 【留名】:111 【人照】:10 【颜值】:10 【身材】:10 【服务】:10 【态度】:10 【环境】:10 【综合】:10 【过程】:四刷妮妮了,老熟人了,妮妮并没有因为我四刷而减少服务内容,依旧的毒龙蛇纹69应有尽有,不得不提一嘴,她的毒龙真的很爽,舌头特别灵敏,服务特别齐全,少有的嫩妹带服务,听说之前也是专业培训过,身材一流,皮肤很白,胸大真胸,胸型完美,不下垂,165左右身高,聊天挺舒服,不做作,会来事,情绪价值很满,工作太忙,每次来都能放松一下自己,妹妹也不催钟,本人比照片好看,妮妮妹妹也是做生意投资失败,才上班,平时不开课都在努力工作,大家多多支持吧,在这里也希望妮妮,早日上岸!

31 Jul 2026, 10:36 UTC≈2,510 views1 reactionsread 31 August 2026
Video

好久不见,小护士妮妮回无锡啦~ 无锡开课啦 @nini9986

1

5 Jul 2026, 04:28 UTC≈3,290 views0 reactionsread 31 August 2026

休息啦,消息平时就不看啦,多多见谅哦

27 Jun 2026, 05:57 UTC≈4,050 views2 reactionsread 31 August 2026
Photo

#宜溧长报告 @YXchaguan 声明:所有报告均带有个人主观色彩,报告仅供参考,请理性看待! ---------【基本信息】---------- 【报告类型】:普通 【提交日期】:2026-06-26 【报告日期】:26/6/26 【老师】:妮妮 【老师账号】:@nini9986 【评价人】:纯粹AAA ---------【客观评分】---------- 【综合评分】:9 【身材评分】:9 【颜值评分】:9 【人照评分】:9 【态度评分】:9 【服务评分】:9 【环境评分】:9 ---------【主观评语】---------- 【服务详情】:关注妮妮很久了,终于等到老师宜兴支教,抽奖居然还中了一张回馈券,于是约第二天,头课已经不在了 ,宜兴的兄弟下手真快啊😂。熟悉的地方,轻车熟路,开门一看老师,和图片一样,颜值身材都不错,付完水费,已经忍不住上下其手,先满足一下手瘾。脱光衣服去洗澡,仔细看了下老师,极品微胖身材,胸很大屁股

2

Showing the 12 most recent of 20 posts we hold for @xiaogushinini. 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.

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

“妮妮秘密基地😇” (@xiaogushinini), 1,367 subscribers as measured 18 September 2026. Telegram Register, tgregister.com/channel/xiaogushinini.

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.