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Channel

西安【认证榜】

@xianpd

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

38,368subscribers

+3,440 since we began measuring on 12 August 2026

Risers and fallers across the register · movement among entries of 31,623–100,000.

Register entry

Telegram ID-1002460520771
TypeChannel
Username@xianpd
Description认证联系: @TShengdi_bot 西安交流群: @xianjlq 🎫个人/中介/会所/外围 认证中心 只做最真实的娱乐资源,真实即可认证 认证通过即可公示!
CreatedBetween 1 September 2024 and 31 March 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded12 August 2026
Last confirmed live25 September 2026
Measurements held29
Confirmed unchanged1 time, most recently 25 September 2026
On Telegramt.me/xianpd

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 9 September 2026 and assigned it the closest of 31 fixed categories, at 50% 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

34,92838,36836,64812 August 2026 — 34,928 subscribers12 August 2026 — 34,928 subscribers13 August 2026 — 34,970 subscribers14 August 2026 — 35,233 subscribers16 August 2026 — 35,273 subscribers17 August 2026 — 35,336 subscribers18 August 2026 — 35,353 subscribers19 August 2026 — 35,338 subscribers20 August 2026 — 35,421 subscribers21 August 2026 — 35,542 subscribers22 August 2026 — 35,549 subscribers24 August 2026 — 35,612 subscribers25 August 2026 — 35,708 subscribers26 August 2026 — 35,716 subscribers27 August 2026 — 35,821 subscribers28 August 2026 — 35,945 subscribers29 August 2026 — 35,983 subscribers30 August 2026 — 35,955 subscribers31 August 2026 — 36,058 subscribers1 September 2026 — 36,159 subscribers2 September 2026 — 36,231 subscribers3 September 2026 — 36,245 subscribers5 September 2026 — 36,442 subscribers9 September 2026 — 36,750 subscribers11 September 2026 — 36,871 subscribers13 September 2026 — 36,660 subscribers15 September 2026 — 36,856 subscribers17 September 2026 — 37,173 subscribers25 September 2026 — 38,368 subscribers12 August 202625 September 2026
29 measurements spanning 43 days, net +3,440. 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 34,412–38,884 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 29
Measured (UTC)SubscribersChange
25 Sept 2026, 01:5838,368+1,195
17 Sept 2026, 07:4037,173+317
15 Sept 2026, 04:3736,856+196
13 Sept 2026, 15:4036,660-211
11 Sept 2026, 17:1636,871+121
9 Sept 2026, 05:4236,750+308
5 Sept 2026, 19:4236,442+197
3 Sept 2026, 19:1736,245+14
2 Sept 2026, 14:3336,231+72
1 Sept 2026, 12:0836,159+101
31 Aug 2026, 10:0636,058+103
30 Aug 2026, 11:2435,955-28
29 Aug 2026, 09:5735,983+38
28 Aug 2026, 07:1735,945+124
27 Aug 2026, 09:4435,821+105
26 Aug 2026, 09:1735,716+8
25 Aug 2026, 05:4235,708+96
24 Aug 2026, 06:1635,612+63
22 Aug 2026, 16:0435,549+7
21 Aug 2026, 06:5335,542first reading

Engagement

34 posts held, back to 11 August 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 79 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
5.26%
avg views ÷ 38,368 subscribers
Avg views / post
2,020
22 posts measured
Reaction rate
0.171%
reactions ÷ views · ER floor
Posts in window
22
of 34 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 28 September 2026
Posts held34 (11 August 2026 – 28 September 2026)
Views total44,430
Reactions total76
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken29 Sept 2026, 15:08 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
≈1,820
Videos
≈340
Links
≈77

Lifetime counters from Telegram’s own channel header, read 29 September 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.

Video runtime
2m 43s
Average length
8s

Measured directly from 20 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

118 reactions across 34 posts, in 8 distinct kinds. The most used accounts for 35.6% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤4235.6%
🔥3328.0%
👍2924.6%
👎54.24%
😁54.24%
👌21.69%
👏10.847%
🥰10.847%

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 34 of the 34 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 118 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 34 most recent posts we hold, published 11 August 2026 to 28 September 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

28 Sept 2026, 11:43 UTC≈1,140 views1 reactionsread 29 September 2026
Photo

【老 师 艺 名】#糯糯 【所 在 位 置】#西安 #高新 【茶 位】#4P #7PP 【服 务 类 型】#全套 【联 系 方 式】@gaoxin_79731 【老 师 频 道】@gerenpindao8282 【双向机器人】@chuanhuatong8289_bot 备注: #个人老师 #视频认证

🔥1

28 Sept 2026, 06:17 UTC≈1,210 views3 reactionsread 29 September 2026
Photo

【老 师 艺 名】#岁禾 【所 在 位 置】#西安 #未央 【茶 位】#6P #11PP 【服 务 类 型】#全套 【联 系 方 式】@suihe2008 【老 师 频 道】@suihegfh 【双向机器人】@suihekjcf_bot 备注: #个人老师 #视频认证

❤1👍1🔥1

27 Sept 2026, 03:05 UTC≈2,340 views5 reactionsread 29 September 2026
Photo

心动💗世界 主题莞式会所 #西安 📱📱八大主题房间 尽享心动💓 📱📱📱 各类情景再现,麻豆剧情演绎 如果普通玩法不满足那🤓🤓🤓🤓 📱 上百套情趣制服,丝袜高跟鞋盛宴 📱 搭配各类皮鞭眼罩道具类玩转4T 📱 00后美女无套口爆,深入体验插入 😀更有莞式十八式之红绳空中飞人 😀又有倒立旋转飞人吹箫 😀再现水磨干磨莞式spa 😀😀😀😀😀😀😀😀😀😀😀 🤣全场海选,组选,每天出勤👍👍 ➕ 🤣主打嫩模,各类兼职,KTV小妹下海捞金 🤣🤣🤣 停车方便😀送红牛中华香烟😀 😀😀😀😀😀😀😀😀😀😀😀 📱📱🤣🤣 🤣🤣🤣🤣 客服号 : @hhhuoddd 双向限制: @hhuodbot 频道: @xingdunai

❤3👍1🔥1

26 Sept 2026, 15:35 UTC≈2,360 views3 reactionsread 28 September 2026
Photo

💞 #西安 唯一独家【千叶·日式裸身风俗泡泡浴】 免费提供制服👗蕾丝👙黑白袜👠,半裸和全裸两种全面且深度的体验(胸手足出) 日式舒缓(🛁大浴缸泡浴)➕玉足戏水,让细腻的泡沫包裹全身,独家传承日式泡泡浴技艺🪭,纯口啤服务,私密性很好,温柔细腻的手法带来极致放松体验。舒缓压力,唤醒身体的每一处感官。👍 高能日本特色AV椅互动助浴,梦境级前列腺高潮体验、穿插轻度sm体验😌独创二代抓龙筋手法、冰火石三角区经络疏通、丝袜捆绑脱敏、三起三落龟责脱敏训练、AV级寸止榨精,引导了解和运用自己的副交感神经系统,助您坚挺、延时😉 ⚡️浪漫之旅:798/70分钟 ⚡️极致花欲:998/90分钟 🧸营业时间:中午12点到凌晨⭐️ 上课预约地址:高新大寨路、未央龙首原 详情咨询TG☎️: @qylspy 双向机器人TG☎️: @qylspy520bot 频道TG👨‍👩‍👧‍👧: @clbfpd

❤1👌1👍1

22 Sept 2026, 09:11 UTC≈2,670 views3 reactionsread 28 September 2026

【留名】:XYZ 【位置】:#西安 #未央 【时间】:2026-09-20 【老师】:#伊恋 【联系】:@yilian22bot 【人照】:9成以上 【颜值】:不算惊艳但不失高雅 耐看型好看 【身材】:胸、bbw 【服务】:xcz🐍69 【过程】:伊恋的优秀夸一下,一切顺畅简单,约课提前不要收定金。伊恋好似邻家妹妹一般,完全像视频和照片中那种略微精神气,简单闲聊几句,本人破冰拉胯可以忽略,交水费进入流程。冲洗过后床上等妹妹冲洗完毕,伊恋上床后环抱着躺在身边,简单聊了聊,已按耐不住,转身望着老师,老师便凑了上来,慢慢亲吻,由浅到深从舌尖碰撞到互相吮吸嘴唇,一边舌一边摸着欢乐豆,老师属于反馈比较含蓄那种,需要慢慢对待,经过一段时间刺激妹妹才慢慢进入状态舌的更投入。口活环节,老师口的比较温柔但是认真,先是手扶着牛子慢慢吮吸,慢慢的放下手上下蛄蛹,此时看着妹妹侧脸兽性大发向上顶,不一会儿妹妹便噎的受不了嘴里拉丝。轮到我来,看着老师的白…

👏1🔥1😁1

22 Sept 2026, 09:09 UTC≈2,510 views4 reactionsread 28 September 2026

【验证留名】:大水牛 【上课时间】: 9-17 【老师花名】:#琳琳 【位置坐标】:#江宁 【上课费用】:600 【服务内容】:课表都有认真做,配合默契 【出击体验】:见面后老师的态度很友好,很爱笑的小姑娘。第一感觉就是很年轻,嫩妹,青春可爱,🐻型很漂亮,粉粉嫩嫩,有点爱不释手。该有的服务都有,比较喜欢的项目,问老师可不可以,得到的都是肯定的回答,情绪价值给的很到位。爱爱的时候能明显感觉到yd里面的收缩,夹的很紧很舒服,正面能看着老师清纯又诱惑的小脸,摇晃着嫩🐻的美妙肉体,不由得生出满满的罪恶感。来南京出差的第一次cj,印象深刻,回味无穷啊! 【优点缺点】:很年轻的妹妹,身材前凸后翘,特别是屁股看着就欲罢不能 【推荐程度】:值得推荐👍 …

❤2👍1🔥1

20 Sept 2026, 16:09 UTC≈3,650 views4 reactionsread 28 September 2026
Photo

【老 师 艺 名】#笑笑 【所 在 位 置】#西安 #碑林 【茶 位】#7P #12PP 【服 务 类 型】#制服 #调情 #69式 【联 系 方 式】@Xiaoxiaoham1 【老 师 频 道】@Xiaoxbaby1 【双向机器人】@yongydhgm_bot 备注: #个人老师 #视频认证

🔥2❤1👍1

20 Sept 2026, 03:19 UTC≈1,710 views3 reactionsread 27 September 2026
Photo

【老 师 艺 名】#蝴蝶 【所 在 位 置】#西安 #未央 【茶 位】#7P #15PP 【服 务 类 型】#全套 【联 系 方 式】@XA03hero 【老 师 频 道】@hudiehero000000 【双向机器人】@hudieherobot 备注: #个人老师 #视频认证

👍1🔥1😁1

16 Sept 2026, 09:44 UTC≈2,030 views4 reactionsread 27 September 2026
Photo

【老 师 艺 名】#梦瑶 【所 在 位 置】#西安 #高新 【茶 位】#5P #9PP 【服 务 类 型】#全套 【联 系 方 式】@mengyao218 【老 师 频 道】@mengyao2188 【双向机器人】@mengyao21_bot 备注: #个人老师 #视频认证

❤2👍1🔥1

16 Sept 2026, 02:41 UTC≈1,830 views9 reactionsread 26 September 2026
Photo

【老 师 艺 名】#娜娜 【所 在 位 置】#西安 #未央 【茶 位】#3P #5PP 【服 务 类 型】#全套 【联 系 方 式】@Xa200317 【老 师 频 道】@nanazi2026 【双向机器人】@nhnaanbot 备注: #个人老师 #视频认证

👎5❤1👌1👍1🔥1

15 Sept 2026, 09:56 UTC≈2,440 views4 reactionsread 20 September 2026
Photo

【老 师 艺 名】#月亮 【所 在 位 置】#西安 #未央 【茶 位】#6P #10PP 【服 务 类 型】#全套 【联 系 方 式】@yueliangabl 【老 师 频 道】@gpUMeO 【双向机器人】@yutudianbot 备注: #个人老师 #视频认证

❤2👍1🔥1

15 Sept 2026, 08:34 UTC≈2,360 views3 reactionsread 19 September 2026
Photo

【老 师 艺 名】#乔乔 【所 在 位 置】#西安 #雁塔 【茶 位】#6P #12PP 【服 务 类 型】#全套 【联 系 方 式】@qiaoqiao52111 【老 师 频 道】@qiaoqiao5201111 【双向机器人】@qqdzl1122bot 备注: #个人老师 #视频认证

❤1👍1🔥1

Showing the 12 most recent of 34 posts we hold for @xianpd. 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.

Mentions

Named by 2 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.

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

“西安【认证榜】” (@xianpd), 38,368 subscribers as measured 25 September 2026. Telegram Register, tgregister.com/channel/xianpd.

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.