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Channel

小芳花园

@xiaofangyiwu

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

179subscribers

+12 since we began measuring on 15 October 2026

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

Register entry

Telegram ID-1004322130075
TypeChannel
Username@xiaofangyiwu
CreatedBetween 1 June 2026 and 31 August 2026 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded15 October 2026
Last confirmed live15 October 2026
Measurements held2
Confirmed unchanged1 time, most recently 15 October 2026
On Telegramt.me/xiaofangyiwu

Growth

16717917315 Oct 2026, 08:22 — 167 subscribers15 Oct 2026, 12:48 — 179 subscribers15 Oct 2026, 08:2215 Oct 2026, 12:48
2 measurements taken within a single day, net +12. 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 165–181 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
15 Oct 2026, 12:48179+12
15 Oct 2026, 08:22167first reading

Engagement

17 posts held, back to 12 September 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
462.3%
avg views ÷ 179 subscribers
Avg views / post
828
10 posts measured
Reaction rate
0.127%
reactions ÷ views · ER floor
Posts in window
10
of 17 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 7 of 10 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 14 October 2026
Posts held17 (12 September 2026 – 14 October 2026)
Views total8,275
Reactions total8
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken15 Oct 2026, 08:22 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
7s
Average length
7s

Measured directly from 1 video 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

17 reactions across 10 posts, in 2 distinct kinds. The most used accounts for 70.6% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤1270.6%
💯529.4%

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 11 of the 17 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 17 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 17 most recent posts we hold, published 12 September 2026 to 14 October 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

1 Oct 2026, 06:00 UTC768 views1 reactionsread 15 October 2026

【义乌赏颜阁】 https://t.me/ywsyg8 【验证时间】:2026-10-01 【老师名字】:芳芳 【老师账号】:@fangfangyiwu 【验证留名】:王一勃(i葱花宝宝,i芳芳。禁欲中) 【人照相似】:8 【颜值身材】:9 【服务评分】:10 【态度评分】:10 【课室环境】:9 【体验过程】:嘿嘿 拿到出击金果断选择我最爱的芳芳老师出击,约第三次咯,嘿嘿😍,约好时间 到点到位 老师还是穿着视频中的服饰,很棒,熟悉之后老师也很放的开,褪去衣物,进去里面开水试水温,好了进去,站着就行,老师正反面帮洗,出来擦干 躺床上,老师问我怎么玩(要不要服务这些)我直接让老师帮忙按摩 按了一会,老师汗都出来了 打开空调,然后我手指戴套,在老师的小骚逼里面就是扣啊扣啊,一会水出了不少,直接戴套提枪上马,给老师一顿干啊,今天状态不错 (十几天没出击了) 换了好几个姿势,听着肉体碰撞的啪啪啪声,顺利出货,这里科普一下,鼓掌的啪啪声跟…

❤1

27 Sept 2026, 08:59 UTC891 views2 reactionsread 15 October 2026

哥哥们要约的抓紧哦,那是姨妈休息了☺️

❤2

24 Sept 2026, 05:04 UTC≈1,060 views2 reactionsread 15 October 2026

【金华义乌福利社】@yiwugo 【评价时间】:2026-09-24 【老师名字】:芳芳 @fangfangyiwu 【验证留名】:三天饿九顿 【人照颜值】:8.5 【身材点评】: 一般身材 【老师类型】:服务型少妇 【相处感受】: 很舒服,听话,主动 【交通便利】:万界门口随便停 【过程描述】: 凌晨临时约的,芳芳老师回复了,就直接约了过去,遥控上楼,人照,9分像,穿着蕾丝暴乳裙,还是不错的,聊了几句直接交了水费,就一起洗澡了!全自动陪浴,出来给你擦干净,残废状态上床给你ab面服务,还有毒龙,课表有的都有,确实不错的,结束完,都有点迷迷糊糊了,给你嗦鸡儿,口的也深,就立马醒了过来,带套女上,也是很会摇的,出水量也多,后面就是主动酷酷干,就不细说了,干了20分钟,成功出水,床单都湿了一块,还是很不错的少妇 【总结】:课表有的都有,服务也不错,全自动,性价比高,服务型少妇必选,300确实很不错的 最新半价、白嫖福利:htt…

❤2

20 Sept 2026, 15:44 UTC≈1,170 views1 reactionsread 15 October 2026

【金华义乌福利社】@yiwugo 【评价时间】:2026-09-20 【老师名字】:芳芳 @fangfangyiwu 【验证留名】:缅北腰王烧烤(i葱花宝宝,i带眼镜的瑶瑶.禁欲中) 【人照颜值】:8 【身材点评】: 8 【老师类型】:少妇 【相处感受】: 特别亲切 越熟悉老师越喜欢,真的好可爱 【交通便利】:交通便利,外面可以停车,可以从地下车库直达课室 【过程描述】: 过了几天,又像我最爱的芳芳老师了,立马中午约课,晚上九点半,然后到点到位,提前到了 老师在里面换衣服,等了一会 开门老师粉色上衣 豹纹短裙 进门换鞋,上次自己的鞋太滑差点摔跤,然后进去洗澡,老师两面都帮忙洗打沐浴露,还调皮的吸了一下小弟弟,(我这里是不要口的),出来擦干身子,老师上来上活,过水吸皮毒龙,口交 很舒服,然后直接给老师添上小妹妹了,老师很害怕这个,每次都被舔的嗷嗷叫只想要,老师b受不了给我整兴奋了,直接舔了好一会,老师要求小弟弟操,但是就是不…

💯1

16 Sept 2026, 05:42 UTC≈1,360 views3 reactionsread 15 October 2026

【金华义乌福利社】@yiwugo 【评价时间】:2026-09-15 【老师名字】:芳芳 @fangfangyiwu 【验证留名】:缅北腰王烧烤(i葱花宝宝,必日) 【人照颜值】:8 【身材点评】: 8 【老师类型】:少妇 【相处感受】: 特别棒,亲和力包容性都很强 【交通便利】:交通方便,小区附近都可以停车 【过程描述】: 本来想抢工兵去的,没抢到,可惜了,然后我中午的时候问了老师可否能接晚上的课,老师答应后问是否要定金,老师说不需要,这里提一嘴,大家最好是真要去了再问老师,要不老师被鸽多了,后面没办法全额面付了😭,到点到了地方,老师开门迎接进课室,套间,外面有客厅,沙发,浴室在课室旁边,浴室有点小,两人一起挺挤的,洗澡基本不用自己动,站着就行,老师会两面都洗干净的,出来的时候老师会帮擦干净,然后上床,老师会胸推,然后还有一个小环节,挺有意思,但是不知道叫什么,准备毒龙但是我没要,这里老师会推荐双飞,有双飞的老师都会有这…

❤2💯1

Showing the 12 most recent of 17 posts we hold for @xiaofangyiwu. 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 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 15 October 2026 — this entry's latest reading, not the date you are reading this.

“小芳花园” (@xiaofangyiwu), 179 subscribers as measured 15 October 2026. Telegram Register, tgregister.com/channel/xiaofangyiwu.

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.