Channel
@yaoyaodejia1
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
1,282subscribers
+161 since we began measuring on 17 August 2026
Risers and fallers across the register · movement among entries of 1,000–3,162.
| Telegram ID | -1003920724937 |
|---|---|
| Type | Channel |
| Username | @yaoyaodejia1 |
| Description | 私聊https://t.me/yaoyao0001 🤖机器人：https://t.me/Yaoyaoisbot |
| Created | Between 1 April 2026 and 15 August 2026 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 16 September 2026 |
| Last confirmed live | 16 September 2026 |
| Measurements held | 11 |
| On Telegram | t.me/yaoyaodejia1 |
Adult — 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 18 September 2026 and assigned it the closest of 31 fixed categories, at 56% 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.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 16 Sept 2026, 15:22 | 1,282 | no change |
| 15 Sept 2026, 06:56 | 1,282 | -20 |
| 11 Sept 2026, 15:17 | 1,302 | -237 |
| 7 Sept 2026, 01:20 | 1,539 | -5 |
| 2 Sept 2026, 03:54 | 1,544 | +527 |
| 30 Aug 2026, 05:03 | 1,017 | -11 |
| 27 Aug 2026, 02:38 | 1,028 | -6 |
| 24 Aug 2026, 13:07 | 1,034 | -8 |
| 21 Aug 2026, 05:03 | 1,042 | -89 |
| 18 Aug 2026, 09:26 | 1,131 | +10 |
| 17 Aug 2026, 15:15 | 1,121 | first reading |
17 posts held, back to 15 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 1 page of Telegram’s post history, 20 posts per page.
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 4 of 14 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 13 September 2026 |
|---|---|
| Posts held | 17 (15 August 2026 – 13 September 2026) |
| Views total | 10,788 |
| Reactions total | 2 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 16 Sept 2026, 15:22 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.
Lifetime counters from Telegram’s own channel header, read 16 September 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.
2 reactions across 2 posts, in 1 kind.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 2 | 100.0% |
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 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 2 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 15 August 2026 to 13 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.
【时间】：2026-09-11 【老师】：瑶瑶 【留名】：小海 123 【评价】：👍 好评 【人照】：7 【颜值】：8 【身材】：8 【服务】：9 【态度】：9 【环境】：8 【综合】：8.17 【过程】：【验证时间】9月11日 【修车费用】1p/半价 【颜值身材】颜值7分 身材8分 【服务内容】课表都有， 69 丝袜 【服务态度】服务投入，无敷衍，主动，听话 【优点缺点】 优点: 1.够瘦，服务好 2.听话指哪打哪 缺点 1. 与频道有一些小差距 【推荐程度】8分 【体验细节】给完水费就直接开始冲洗，老师帮洗很认真，洗完很快进入状态 熟悉之后慢慢褪去衣服 老师皮肤光滑 果断上手狠狠地摸了一下一遍 这又惊喜到我了 ，毒龙也很舒服，在抽出接近十分钟后顺利出水
【时间】：2026-09-10 【老师】：瑶瑶 【留名】：。 【评价】：👍 好评 【人照】：8 【颜值】：8 【身材】：9 【服务】：9 【态度】：10 【环境】：8 【综合】：8.67 【过程】：老师身材苗条偏瘦，有些许骨感，颜值也不错。坐下先闲聊一会儿，一起洗完后到床上，小小的🐻，一只手能握下。舌吻缠绵一番开始口活舌头挺灵活口的蛮舒服的，换到69，水很快多了起来开始正戏。女上体力还行，坐累了换我臀桥顶，叫声蛮好听，美腿勾住脖子，勾引我猛猛加速，后入腰身纤细，要是臀部大一些观感就更好了，最后换回抱着老师冲刺顺利出货。又唠嗑了一会儿，有时挺幽默的，整体过程轻松愉快，有机会会再约
开课中
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❤1
✨ 命运揭晓时刻 ✨ 广州茶馆-瑶瑶半价券 开奖了 抽奖人数：663，抽奖号数：1260 1. 不会迫降的菜车手 中得：p半价券（必须写报告） 抽奖说明： 1：刷屏、灌水、纯表情、复制粘贴、无意义对话、删除消息等，一律视为无效发言，取消中奖资格！请用心交流！ 2：中奖后7天内出击，完成必须写报告！没出报告的拉黑抽奖！写报告：@gzcg1bot 3：写报告抽500现金和巨量圣晶石！！！ 🔍 杜绝黑幕，点击查看本次开奖全程验证
开课中，有空可以约
🎉 白云区御姐瑶瑶p半价卷 🎁 奖品清单 • p半价优惠卷 × 1 🛡️ 参与条件 • 加入 广州修车协会【探花】 • 加入 瑶瑶的后花园 • 加入 广州修车【探花】娱乐榜 • 加入 （广州探花）娱乐反馈报告 • 参加抽奖后需在 广州修车协会【探花】 内发言10次 └ 群内发送“抽奖进度”查看完成度（每日限5次） • 必须设置用户名 🔮 祝福加持 • 祝福消耗：30探花 • 祝福上限：30次 • 祝福一次增加一个抽奖号，提高中奖率 • 幸运值祝福：支持 幸运值说明 ⌛ 抽选时刻 • 2026-09-06 19:44:00 📜 抽奖说明 ❶刷屏、灌水、纯表情、复制粘贴、无意义对话、删除消息、撤回内容等，一律视为无效发言，取消中奖资格！请用心交流！ ❷请三天内约课，五天内完成上课，因炸号，退群，注销账号等原因，超时未兑换等原因的，不予兑奖！ ❸活动最终解释权归本群管理团队所有。 ⚠️自言自语刷屏再删消息的都会被永久封禁…
瑶瑶的后花园 pinned a photo
💐💐💐开奖了💐💐💐 【骑士团☆ 瑶瑶 半价活动】开奖了 本期总参与人数：205 少女币加成数：11 1、波刘（消息数21 加成数0）获得：半价p 兑奖请联系 @yaoyao0001 谨祝中奖用户大吉大利万事如意 更多资讯请关注
每月红包、半价/白嫖各种福利 广州修车协会【探花】 ： https://telegram.me/GZ08866 广州娱乐总榜单： https://telegram.me/GZYL8866 上榜合作： @gzsbjqrbot
Photo, posted without a caption
瑶瑶的后花园 pinned a photo
Showing the 12 most recent of 17 posts we hold for @yaoyaodejia1. 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.
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.
Named by 3 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.
Names
Channels on the register whose handles appear in this channel's posts.
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.
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 16 September 2026 — this entry's latest reading, not the date you are reading this.
“瑶瑶的后花园” (@yaoyaodejia1), 1,282 subscribers as measured 16 September 2026. Telegram Register, tgregister.com/channel/yaoyaodejia1.
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.