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Telegram profile photo for 南山舒淇

Channel

南山舒淇

@ntf112233

On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Handles named that no longer answer · Cite this entry

1,024subscribers

+79 since we began measuring on 19 August 2026

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

Register entry

Telegram ID-1002228946919
TypeChannel
Username@ntf112233
CreatedBetween 1 June 2024 and 30 September 2024 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded19 August 2026
Last confirmed live6 September 2026
Measurements held6
Confirmed unchanged1 time, most recently 6 September 2026
On Telegramt.me/ntf112233

Growth

9451,02598519 August 2026 — 945 subscribers19 August 2026 — 945 subscribers20 August 2026 — 948 subscribers26 August 2026 — 998 subscribers2 September 2026 — 1,025 subscribers6 September 2026 — 1,024 subscribers1,02419 August 20266 September 2026
6 measurements spanning 18 days, net +79. 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 933–1,037 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
6 Sept 2026, 12:401,024-1
2 Sept 2026, 02:361,025+27
26 Aug 2026, 14:14998+50
20 Aug 2026, 00:17948+3
19 Aug 2026, 13:15945no change
19 Aug 2026, 13:00945first reading

Engagement

20 posts held, back to 9 August 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
26.6%
avg views ÷ 1,024 subscribers
Avg views / post
273
20 posts measured
Reaction rate
0.423%
reactions ÷ views · ER floor
Posts in window
20
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. It is computed over the 10 of 20 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 19 August 2026
Posts held20 (9 August 202619 August 2026)
Views total5,455
Reactions total12
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken19 Aug 2026, 13:15 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
1m 01s
Average length
6s

Measured directly from 11 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

12 reactions across 10 posts, in 3 distinct kinds. The most used accounts for 41.7% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
541.7%
🥰541.7%
💩216.7%

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 10 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 12 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 9 August 2026 to 19 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

19 Aug 2026, 08:06 UTC37 viewsread 19 August 2026
Forwarded from @sz3hdsrp

【深圳三和修车报告】 https://t.me/sz3hdsrp 【学生留名】:小幸运 【出击时间】:8.19 【老师名字】:#南山舒淇 【深圳地区】:#深圳 #南山 【出击消费】:1000P 【颜值身材】:年轻漂亮身材好御姐型 【服务内容】:课本上都有 【上课体验】:刚刷到舒淇,趁着有空就立马约了课,小区高端又好找,离地铁口50米,房间又大又干净,隔音效果不错。小姐姐穿着后妈裙,一下就被完美的S型身材给吸引了,长相又非常好看,个子高,课表描述一致,聊了会,原来是成都的妹妹,一起沐浴,小姐姐帮忙洗白白,科室一次性浴巾这些都有。来到床上享受小姐姐的服务,舔胸,吸舔棒棒,69无异味,小姐姐说我舔的很舒服,受不了后就带上雨伞,先是女上,超舒服的,后面换了几个姿势畅快出水,休息一会,一起沐浴,拥抱告别,小姐姐态度很好。热情又自来熟,还离我那么近,必须还会再返滴 【优点缺点】:服务热情态度好,肤白貌美大长腿 【老师电报】: @bao15

18 Aug 2026, 11:04 UTC128 viewsread 19 August 2026
Forwarded from @szflbg

——枫林体验 https://t.me/szflw 上课时间:8.17 老师花名:南山舒淇 课室位置:#深圳 #南山 老师电报: @bao15888777 颜值身材:年轻漂亮身材好,御姐,🐻大,水多会夹 体验细节:看到频道舒淇妹妹后,感觉是喜欢的类型就提前一天约好了。课室条件非常不错,是我遇到过环境最好的了,对妹妹的第一印象是好高,包臀裙尽显完美身材!最意外的是,妹妹虽然年纪不大,但是性格格外开朗,聊起天来很舒服,像是许久不见的老友。来到床上,一边亲着妹妹粉嫩的乳头一边抚摸着顺滑的肌肤,特别是妹妹骚骚的眼神,口的时候各种眼神杀,让我完全沉浸其中,硬的像铁棒一样。迫不及待带上工具,展开激烈深入交流,先是后入,又翘又大的屁股在撞击下臀浪不断起伏,爱死这圆润的大翘臀!后面累了换成女上,妹妹坐的很深,动的非常投入,最后冲刺顶到最深处狠狠射出全部精华。结束后又聊了一会,看着这魔鬼身材和校花级别的高颜,必须下次再见! 推荐程度:🍁🍁🍁🍁🍁

16 Aug 2026, 12:51 UTC257 viewsread 19 August 2026

派大星出击报告( https://t.me/+2Kbp7dDZd904ZDBk ) 验证留名:搭档 验证时间:8月15号 老师花名:#南山舒琪 城市坐标:#深圳 #南山 上课花费:1000PP 颜值身材:年轻漂亮身材好御姐型,服务型 服务内容:课本上 出击体验:一进门舒淇老师就笑着迎上来,先给我递了瓶水,接着两人聊了会天。看着她边说话还一脸害羞腼腆的样子,特别惹人喜欢。休息一会后两个人一起脱了衣服进浴室洗澡,还是和上次来一样前前后后都洗的很到位, 来到床上,老师的舌头在我两个奶头舔完慢慢往下走,一口把我的老二含住开始亲吸舔,口活还是无敌好,口的我受不了后,我开始给老师反向服务,舔的老师发出阵阵的低吟,接着直接戴伞开干,先传教士的时候老师的小穴已经很湿了,包裹感强,我边传教边和老师亲吻,太爽了,接着换女上,看着老师微红的美颜就是一种享受,在不断的抽插中爽射出货,非常完美的第2次复刷体验,下次继续包个时再复刷! 优点缺点:完美 推荐

15 Aug 2026, 12:25 UTC285 viewsread 19 August 2026
Forwarded from @SZGBBGPhoto

【工兵报告】https://t.me/SZGBBG 【老师艺名】舒淇 【联系方式】 @bao15888777 【所在位置】#深圳南山 【验证留名】 【验证时间】2026年8.15 【修车费用】1000p 【颜值身材】真人漂亮,身材好 【服务内容】共浴,口,69,爱爱,调情,制服丝袜诱惑,课本上都有 【服务态度】10 【优点缺点】很嫩,很紧致,身材好,年轻漂亮 【推荐程度】10 【体验细节】昨晚刚好看到了舒淇老师,赶紧约了今天的头课,晚上看着老师的视频心心念念了很久,才入睡。第二天醒来,跟老师联系了下就直接出发了,按照老师给的地址准时到了,到了课室进来交了水费,老师说要陪浴,我说我习惯独自洗澡,简单冲洗一下擦干在床上等着老师。老师洗完回来一眼看到她身材真是太顶了,胸大腰细,腿又长,dd早意忍不住硬了起来,然后老师扎起头发开始亲亲舔舔服务起来,简直不要太爽,囗活更是无敌棒,随后69,bb嫩嫩的无异味,戴上小雨伞进入正题,女上视觉效果

14 Aug 2026, 10:58 UTC329 viewsread 19 August 2026
Forwarded from @szflbg

——枫林体验 https://t.me/szflw 上课时间:8.13 老师花名:南山舒淇 课室位置:#深圳 #南山 老师电报: @bao15888777 颜值身材:年轻漂亮身材好,御姐 体验细节:约好时间,遥控上楼,课室干净整洁,舒淇老师穿着吊带迎接、前凸后翘大长腿,身材好好!人又漂亮,果断交水费,再简单的聊一会儿去洗澡,共浴,还帮忙擦干,去到房间老师换上情趣,站在大镜子面前,细腰大臀长腿一览无遗!老师的服务细节很到位,舌尖的触碰轻柔且富有挑逗性,几下挑逗就顿时让小弟硬起来,这身材视觉上的冲击力实在太强,开始戴套进入实战,老师开启女上位模式,伴随着饱满胸部的剧烈晃动,这种感官冲击确实让人难以招架。由于老师太顶,加之紧致的包裹感,在加速冲刺中没能抗住,而且还很紧致,体感加观感拉满了,最后在老师的一声“给我”中忍不住被秒了,过程体验感都很棒,下次还会再来! 推荐程度:🍁🍁🍁🍁🍁 温馨提示:审美因人而异,服务亦有不同,报告好坏皆仅

14 Aug 2026, 05:33 UTC385 viewsread 19 August 2026

派大星出击报告( https://t.me/+2Kbp7dDZd904ZDBk ) 验证留名:蓝猫 验证时间:8月13号 老师花名:#南山舒琪 城市坐标:#深圳 #南山 上课花费:1800PP 颜值身材:年轻漂亮身材好御姐型,服务型 服务内容:课本上 出击体验:今次經朋友介紹, 話有一個舌技好的御姐推介, 所以趁无事幹慾望起就果斷出击. 到达小区环境干净安静, 一开門见老师样子超好看, 身材无敌,穿着裙子性感诱惑拉满, 先和老师一起洗澡, 然後躺在床上, 老师純熟灵活的舌技吻遍全身及咪咪, 感覺超爽,在老师温暖爱抚下鷄巴逐漸坚挺, 老师的口活更是一级棒不想停, 差點走火,爱爱的时候先是女上,直接被秒了,休息片刻后,开始二回合,妹妹很紧,会夹,四目相对, 最後我后入用力冲冲刺十數下後爽爆出货。老师开放很会唠嗑不催时间服务都有过程中也很配合有耐心,兄弟及朋友们值得冲。 优点缺点:完美 推荐程度:10分x/满分10.0件(服务,态度)

Showing the 12 most recent of 20 posts we hold for @ntf112233. 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

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

“南山舒淇” (@ntf112233), 1,024 subscribers as measured 6 September 2026. Telegram Register, tgregister.com/channel/ntf112233.

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.