Telegram RegisterThe public register of Telegram
Telegram profile photo for 中华娘|汉服|古装|旗袍🍭

Channel

中华娘|汉服|古装|旗袍🍭

@Chinaniang

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

14,659subscribers

+875 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 10,000–31,623.

Register entry

Telegram ID-1001737988070
TypeChannel
Username@Chinaniang
CreatedBetween 1 December 2021 and 30 April 2023— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live25 August 2026
Measurements held17
Confirmed unchanged1 time, most recently 25 August 2026
On Telegramt.me/Chinaniang

Growth

13,78414,65914,221.57 August 2026 — 13,784 subscribers7 August 2026 — 13,784 subscribers8 August 2026 — 13,833 subscribers9 August 2026 — 13,854 subscribers10 August 2026 — 13,905 subscribers11 August 2026 — 13,958 subscribers12 August 2026 — 13,991 subscribers14 August 2026 — 14,056 subscribers15 August 2026 — 14,130 subscribers16 August 2026 — 14,235 subscribers17 August 2026 — 14,300 subscribers18 August 2026 — 14,361 subscribers19 August 2026 — 14,413 subscribers20 August 2026 — 14,455 subscribers22 August 2026 — 14,528 subscribers23 August 2026 — 14,596 subscribers25 August 2026 — 14,659 subscribers7 August 202625 August 2026
17 measurements spanning 17 days, net +875. 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 13,653–14,790 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
25 Aug 2026, 04:4814,659+63
23 Aug 2026, 22:5814,596+68
22 Aug 2026, 10:2414,528+73
20 Aug 2026, 22:0414,455+42
19 Aug 2026, 22:2214,413+52
18 Aug 2026, 19:4814,361+61
17 Aug 2026, 20:5414,300+65
16 Aug 2026, 21:1314,235+105
15 Aug 2026, 12:4814,130+74
14 Aug 2026, 01:0814,056+65
12 Aug 2026, 19:4313,991+33
11 Aug 2026, 16:2813,958+53
10 Aug 2026, 16:0213,905+51
9 Aug 2026, 16:0813,854+21
8 Aug 2026, 18:1913,833+49
7 Aug 2026, 18:4513,784no change
7 Aug 2026, 18:3813,784first reading

Engagement

13 posts held, back to 3 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 33 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
14.2%
avg views ÷ 14,659 subscribers
Avg views / post
2,080
13 posts measured
Reaction rate
0.395%
reactions ÷ views · ER floor
Posts in window
13
of 13 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 23 August 2026
Posts held13 (3 August 202623 August 2026)
Views total27,103
Reactions total107
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken25 Aug 2026, 02:14 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
17m 30s
Average length
2m 30s

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

107 reactions across 13 posts, in 4 distinct kinds. The most used accounts for 52.3% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
5652.3%
👍2927.1%
❤‍🔥1211.2%
109.35%

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 13 of the 13 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 107reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 13 most recent posts we hold, published 3 August 2026 to 23 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

23 Aug 2026, 10:29 UTC869 views6 reactionsread 25 August 2026
Photo

#过期米线线喵 - #侑子小姐 [49P-327M] #coser #xxxHOLiC #古装

👍3❤‍🔥21

23 Aug 2026, 01:04 UTC≈1,100 views7 reactionsread 25 August 2026
Photo

#不呆猫 - #舰长 #福利 [129P2V-278MB] #B站 #古装 不呆猫这次化身港风古装舰长,129张高清大图加2支短片诚意满满!她以灵动的眼神和俏皮表情,把“舰长”角色穿出别样韵味——不是传统军装,而是古风长裙、薄纱飘带,腰间挂饰细节超带感。场景古色古香,配合暖光滤镜,既有江湖侠气又带一丝福利气息。无论是站立回眸还是抚扇浅笑的瞬间,都抓拍得十分耐看。喜欢古装加俏皮风格的话,这套绝对值得收藏!

51👍1

18 Aug 2026, 03:16 UTC≈3,070 views9 reactionsread 25 August 2026
Photo

#萌芽儿o0 - #龙华妃咲 [64P-904MB] #coser #旗袍 龙华妃咲是《碧蓝档案》里来自山海经高级中学的优雅少女,平时总爱穿着端庄旗袍,带着一丝神秘又温柔的知性气息。这套作品正好抓住她的东方古典韵味——贴身旗袍勾勒出优美线条,缎面光泽与盘扣细节都透着精致感。妆造干净清透,发型和发饰呼应角色的典雅气质,场景也带着安静的画面故事感。64张美图加近1G大包,从半身特写到全身姿态都有收录,适合喜欢旗袍风、东方韵味和蓝档案角色的朋友细细品味。

9

14 Aug 2026, 18:36 UTC≈3,630 views13 reactionsread 23 August 2026
Photo

#不呆猫 - #舰长 #福利 [129P2V-278MB] #B站 #古装 不呆猫化身古风舰长,英气与柔美并存!129P高清大图+2V动态福利,从衣袂纹理到发簪细节都超用心~既有运筹帷幄的端庄气场,又藏着小福利的俏皮瞬间。B站古装控千万别错过,光影质感也很舒服,适合收藏反复欣赏!

👍722❤‍🔥2

13 Aug 2026, 20:29 UTC≈3,700 views13 reactionsread 23 August 2026
Photo

#钛合金TiTi - #小龙女 [103P-676MB] #古装 #coser 历史精选 小龙女作为金庸笔下最经典的古墓派掌门,白衣素颜、清冷绝尘,是无数人心中的白月光~钛合金TiTi这套古风作品,精准抓住了那份不食人间烟火的仙气! 103P高清大图,从幽深古墓到山涧花影,场景层次超丰富!一袭白衣飘逸如雪,妆造干净素雅,眉眼间既有小龙女的疏离感,又藏着几分温柔笑意。 尤其爱那些帷幔轻纱的光影瞬间,仙气直接拉满;执剑回眸的几张又英气逼人,反差感绝佳!古装控必收的宝藏套图,值得反复细品~

8❤‍🔥2👍21

13 Aug 2026, 08:34 UTC≈2,510 views7 reactionsread 17 August 2026
Photo

#Bangni邦尼 - #部落之魂 #印第安紫舞龙 [129P9V-1.25GB] #coser

👍3❤‍🔥211

13 Aug 2026, 06:17 UTC474 views9 reactionsread 13 August 2026
Photo

#修修猫ww - #鸣潮 #绯雪 [36P-843MB] #coser 修修猫ww化身《鸣潮》绯雪,一位在战火与风雪中执着前行的信使。 整套作品36张高清图片,854MB容量,画质细腻,氛围感拉满。 绯雪的标志性银白长发与冰蓝眼眸被精准还原,服装细节和饰品纹理都很有质感。 场景选在雪地与废墟之间,光线处理柔和,既有战斗的苍凉,又有角色独有的温柔。 无论是静态特写还是动态抓拍,都展现出修修猫对角色气质的把握——清冷中带着坚定,飒爽里藏着故事。 喜欢绯雪或《鸣潮》的玩家,这套图绝对值得收藏!

4👍31❤‍🔥1

11 Aug 2026, 07:26 UTC≈1,630 views7 reactionsread 13 August 2026
Photo

#玉汇 ( #Kokuhui) - #神乐巫女の试炼 [139P3V-1.35GB] #coser 原精选,已流出 这位Coser自带一丝清冷又神秘的气质,与「神乐巫女」的设定格外契合。 套装以巫女装束为核心——绯袴、白衣、注连绳与神乐铃,细节精致,层层叠叠很有仪式感。 场景选在古社与薄雾林间,光影柔和中带一点幽玄,仿佛真的走入神明的试炼之地。 139张图片加3段视频,完整记录从舞乐、祈祷到灵力觉醒的过程,画面既神圣又带一点暗黑张力。 喜欢巫女题材、和风氛围或美型Coser的朋友,这一套值得慢慢收藏。

👍411❤‍🔥1

11 Aug 2026, 04:25 UTC≈1,110 views6 reactionsread 13 August 2026
Photo

#Dakki伊 - #崩坏 #星穹铁道 #阮梅[51P1V-339MB] #coser #Dakki伊化身星穹铁道天才科学家阮梅,优雅与知性并存,完美复刻角色气质。 紫色长发飘逸,蝴蝶结与工装细节精致,服装还原度高,尽显学术魅力。 场景与道具搭配用心,营造出模拟宇宙的神秘氛围,科技感十足。 51P高清图片+1段视频,多角度捕捉阮梅的温柔笑颜与冷静眼神,画质清晰。 无论是静态特写还是动态片段,都让人感受到角色背后的故事,值得收藏!

👍41❤‍🔥1

10 Aug 2026, 06:10 UTC≈1,320 views8 reactionsread 13 August 2026
Photo

#小容仔咕咕咕w - #虞美人 [36P-194MB] #旗袍 一袭古典旗袍勾勒出东方美人的曼妙身段,小容仔咕咕咕w化身虞美人,眉眼间尽是温婉与风情。整套作品以柔光、淡彩为主调,搭配团扇、旧木椅等精致道具,复古氛围跃然画面。36张写真的构图从特写到全身皆精心打磨,将旗袍的盘扣、刺绣与开衩细节展现得淋漓尽致,同时融入虞美人的历史幽怨感,兼具妩媚与哀愁。喜欢国风、旗袍控和情绪氛围写真的朋友,这套绝对值得收藏~

4👍21❤‍🔥1

4 Aug 2026, 21:22 UTC≈2,570 views5 reactionsread 10 August 2026
Photo

#蘑菇头 - #会员花絮 #红黑和服[66P1V-2.35GB] #摄影师 #精选 未流出资源

5

4 Aug 2026, 03:42 UTC≈2,700 views9 reactionsread 10 August 2026
Photo

#Neko薇薇 - #改良黑 #旗袍 [35P-225MB] #coser 这位Coser以黑色改良旗袍造型出镜,将传统旗袍的优雅与现代剪裁的利落感融合。暗色系主调中透出神秘气质,搭配精致妆发与点缀道具,层次丰富。35张图收录了不同角度与细节特写,画质清晰,氛围安静而有韵味,适合喜欢东方古典与现代美学碰撞的观众。

9

Showing the 12 most recent of 13 posts we hold for @Chinaniang. 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.

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 25 August 2026 — this entry's latest reading, not the date you are reading this.

“中华娘|汉服|古装|旗袍🍭” (@Chinaniang), 14,659 subscribers as measured 25 August 2026. Telegram Register, tgregister.com/channel/Chinaniang.

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.