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Telegram profile photo for xiaoxing_home

Channel

xiaoxing_home

@xiaoxing_home

On this record: Growth · Engagement · Reactions · Posts · Citations · Cite this entry

376subscribers

+1 since we began measuring on 24 August 2026

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

Register entry

Telegram ID-1002258253018
TypeChannel
Username@xiaoxing_home
CreatedBetween 1 September 2024 and 31 March 2025— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded24 August 2026
Last confirmed live25 August 2026
Measurements held3
Confirmed unchanged1 time, most recently 25 August 2026
On Telegramt.me/xiaoxing_home

Growth

375376375.524 Aug 2026, 11:30 — 375 subscribers24 Aug 2026, 11:45 — 375 subscribers25 Aug 2026, 01:04 — 376 subscribers24 Aug 2026, 11:3025 Aug 2026, 01:04
3 measurements taken within a single day, net +1. 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 375–376 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
25 Aug 2026, 01:04376+1
24 Aug 2026, 11:45375no change
24 Aug 2026, 11:30375first reading

Engagement

19 posts held, back to 8 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 pageof Telegram’s post history, 20 posts per page.

ERR · 30 days
130.3%
avg views ÷ 376 subscribers
Avg views / post
490
3 posts measured
Reaction rate
0.22%
reactions ÷ views · ER floor
Posts in window
3
of 19 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 1 of 3 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 6 August 2026
Posts held19 (8 March 20266 August 2026)
Views total1,470
Reactions total1
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken24 Aug 2026, 11:45 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.

Reaction mix

3 reactions across 2 posts, in 1 kind.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
3100.0%

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 4 of the 19 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 3reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 19 most recent posts we hold, published 8 March 2026 to 6 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

25 Jul 2026, 05:24 UTC817 viewsread 24 August 2026
Forwarded from @dlcarplay_bot

【时间】:2026-07-25 【老师】:#小星 【留名】:匿名 【人照】:9.5 【颜值】:9.5 【身材】: 【服务】:10 【态度】:10 【环境】: 【综合】:9.75 【过程】:关注老师有段时间了,一直没有出击,今天有空约了老师小时,见面老师小小的,没有距离感,很亲切,过程很舒服,老师的服务很细致,要求都尽量满足,像女友的感觉,老师身材也好,过程真的特别舒服,真是特别值得

30 Jun 2026, 10:32 UTC≈1,120 viewsread 24 August 2026
Forwarded from @dlcarplay_botPhoto

🈶🉑👍✅ 【时间】:2026-06-30 【老师】:#小星 【留名】:专啃沙发腿的哈士奇 【人照】:9 【颜值】:9 【身材】:9 【服务】:10 【态度】:10 【环境】:9.5 【综合】:9.42 【过程】:周日加班,干到下午脑子抽筋,身体燥热,搜了下附近,选了一直想去奈何时间碰不上的小星。 准时到达停好车,路边很多停车位,蛮方便。发消息给老师,等了两三分钟,老师下楼来接,穿了一身运动装带个帽子,英姿飒爽的。进门后,态度热情第一时间问我喝什么,问我热不热,要开空调让我休息凉快点。 简单冲洗进屋趴下开始B面,一通漫游还连夸我屁股翘,我说你的也不遑多让。因为周五练的腿,该死的保加利亚深蹲折磨得我这两天坐也不是躺也不是,爬楼梯就已经痛苦面具了,搞得兄弟也不是很有精神,B面都没啥反应,好在小星口活神乎其技,拯救我的疲软,A面一通操作,直接一柱擎天,我手也没闲着,摸了摸蜜雪,发现已经水漫金山了,摸了两下她说痒,瞬间激起我的胜负欲,我说

21 Jun 2026, 13:17 UTC≈1,070 viewsread 24 August 2026
Forwarded from @dlreport6Photo

【时间】:2026-06-18 【老师】:#小星 【留名】:辽东半岛第一纯情 【人照】:10 【颜值】:10 【身材】:10 【服务】:10 【态度】:10 【环境】:10 【综合】:10 【过程】:夯爆了夯爆了夯爆了!重要的事要说三遍,小星老师直接排名顶夯。环境是个人租的房子,老师下楼带你,小区很安静隐蔽,自己租的房子环境特别好,温馨干净,洗澡的水和花洒不是公寓能碰瓷的。见老师第一面就震惊了,温温柔柔白白净净,说话也是柔声细语的,真女友感。摸了老师屁股一下,感觉摸到了比基尼小姐的屁股,特别翘特别紧,duangduang的。上楼后老师先给拿水喝,老师换了一套巨性感的小衣服,配上老师无比曼妙的身材,二弟直接敬礼。服务分为ab面,老师节奏无敌,循序渐进,把心中的冲动慢慢全勾引出来,而且老师的活真的特别特别细,口活更是无敌,全程差点把持不住。服务完后直接提枪上马,小星老师的妹妹很紧致,刚开始女上都夹得我疼的地步。无论前后都是特别舒服。

19 Jun 2026, 00:22 UTC≈1,040 viewsread 24 August 2026

祝宝宝们端午安康,心想事成,财源广进😘😘😘

Showing the 12 most recent of 19 posts we hold for @xiaoxing_home. 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.

Citation-graph rank

Citation-graph rank — 1,018,203 of 1,620,455entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.

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

“xiaoxing_home” (@xiaoxing_home), 376 subscribers as measured 25 August 2026. Telegram Register, tgregister.com/channel/xiaoxing_home.

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.