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Telegram profile photo for 丸子花园~

Channel

丸子花园~

@dududexiaojia

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

300subscribers

+52 since we began measuring on 26 September 2026

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

Register entry

Telegram ID-1002792359967
TypeChannel
Username@dududexiaojia
CreatedBetween 1 June 2025 and 30 September 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded26 September 2026
Last confirmed live4 October 2026
Measurements held3
Confirmed unchanged1 time, most recently 4 October 2026
On Telegramt.me/dududexiaojia

Growth

24830027426 September 2026 — 248 subscribers26 September 2026 — 248 subscribers4 October 2026 — 300 subscribers26 September 20264 October 2026
3 measurements spanning 8 days, net +52. 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 240–308 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
4 Oct 2026, 11:55300+52
26 Sept 2026, 21:22248no change
26 Sept 2026, 20:47248first reading

Engagement

14 posts held, back to 8 January 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 1 page of Telegram’s post history, 20 posts per page.

ERR · 30 days
20.3%
avg views ÷ 300 subscribers
Avg views / post
61.0
2 posts measured
Reaction rate
—
this channel exposes no reaction counts
Posts in window
2
of 14 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 26 September 2026
Posts held14 (8 January 2026 – 26 September 2026)
Views total122
Reactions total—
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken26 Sept 2026, 21:22 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
8s
Average length
4s

Measured directly from 2 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

3 reactions across 3 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 14 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 3 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 14 most recent posts we hold, published 8 January 2026 to 26 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

26 Sept 2026, 08:56 UTC28 viewsread 26 September 2026
Photo

🐖【珠海/中山】学生会每日更新🐖 👣 艺 名:#凯丽 😃 位 置:#珠海 #香洲 👉 联系: @dudukukuoo 🥰 频道: https://t.me/dududexiaojia 💸 700一节课 两节课1300 👉 双向:@dudududexbot ❗️ 联系老师时(说注学生会推荐) 😜 有上榜请联系 “学生委员” 🔹🔹🔹🔹🔹🔹🔹🔹🔹🔹 ✍️课后作业: 😝🤩😜🤪🥰🥰🥰🥰🥰🥰 😏学生交流 / 上榜联系🥰

26 Jan 2026, 06:23 UTC980 views1 reactionsread 26 September 2026
Forwarded from @GZsnyjbgj

【少御报告】https://t.me/GZsnyjhj 【老师艺名】凯丽 【联系方式】@dudukukuoo 【所在位置】海珠 【验证留名】李霸 【验证时间】1.26 【修车费用】800 【颜值身材】颜值高很甜 【服务内容】课表都做 【服务态度】9 【优点缺点】9 【推荐程度】9.2 【体验细节】遥控上楼,人照一致程度可以给9.5分,甚至比照片还好看。身材和照片也无差别,腰臀比是凹凸有致,凶器真大,一只手完全不够摸,肉感很软,胸型很好看,可以放心冲。最主要是老师很擅长主动和前戏,提前跟老师说好,一进门就开始相拥,两人的手互相游离,欲火焚身。亲的时候老师眼神迷离十分销魂,隔着裙揉捏老师软糯Q弹的大屁股太带劲了。口的时候,无齿感,无可挑剔,69时给老师一些刺激就会很猛。接下来123,几乎所有姿势都尝试了。课室场景很丰富。老师无时不刻都在挑逗你,撩拨你的心弦。最后忍不住出货,恋恋不舍离开 ♥️温馨提示: 以上仅代表个人体验,报告仅供…

❤1

14 Jan 2026, 06:32 UTC855 viewsread 26 September 2026
Forwarded from @GZsnyjbgj

【少御报告】https://t.me/GZsnyjhj 【老师艺名】凯丽 【联系方式】@dudukukuoo 【所在位置】海珠 【验证留名】犀利热 【验证时间】1.14 【修车费用】800 【颜值身材】丰满 【服务内容】课表 【服务态度】9 【优点缺点】9 【推荐程度】9.5 【体验细节】第一次来体验宝宝老师,感觉特别好特别爽,谁来谁知道啊,只有体验过的才知道这种姐姐服务到底有多贴心,刚好今天有空,约老师体验一下,当时只是来想体验一下姐姐这种御姐可爱风的味道,没成想太舒服了,舌头舔哪里都软软的,还有少许按摩,👄的非常舒服,次级,服务特别好而且又温柔,本来还是有点紧张害羞的,但是在姐姐温柔的话语中慢慢的就放松了,之后的流程就是慢慢享受姐姐的伺候,全程女上,这个姿势太舒服了,而且姐姐特别讲卫生,一次性浴巾一次性床单,喜欢服务好的无脑往姐姐那冲就好了,绝对值得,这个价格也合理,居听说还可以口爆,只可惜时间不够,意犹未尽,下次必须包时,…

11 Jan 2026, 09:15 UTC761 views1 reactionsread 26 September 2026
Forwarded from @GZsnyjbgj

【少御报告】https://t.me/GZsnyjhj 【老师艺名】凯丽 【联系方式】@dudukukuoo 【所在位置】天河 【验证留名】申金 【验证时间】1.11 【修车费用】800 【颜值身材】老师长得像一个网红 【服务内容】课表 【服务态度】全自动 【优点缺点】无缺点 【推荐程度】十分还会来的 【体验细节】本人真实报告,服务态度好,课表上服务都有,课室环境极好,跟老师预约好时间,开车前往。在老师的指挥下上楼,看到老师后很惊喜,跟照片基本一致,身材很好,付完课费闲聊了会,洗浴也很细心,洗完躺上床开始服务,服务过程中极度诱惑,从见面开始肉棒就处于一直挺立的状态,老师很主动握住,用手帮我揉捏放松,口活也很好,口的我有点受不了,直接进入正题,带上tt之后我喜欢在上面,妹子很配合,差点被秒,叫床声真好听,最后关头一直浪叫让我把精液射给她,射完整个人很通透,一次愉快的出击体验,值得推荐!冲冲冲 ♥️温馨提示: 以上仅代表个人体验,报…

❤1

Showing the 12 most recent of 14 posts we hold for @dududexiaojia. 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 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.

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 4 October 2026 — this entry's latest reading, not the date you are reading this.

“丸子花园~” (@dududexiaojia), 300 subscribers as measured 4 October 2026. Telegram Register, tgregister.com/channel/dududexiaojia.

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.