#菲菲 已在「老友会」验证上榜 👇👇👇👇👇👇👇👇 查看 距离 营业时间 : t.me/szxglyhOneBot?startapp=td_8050643799 👆👆👆👆👆👆👆👆 打造纯净生态,不负信赖与热爱。 加群/频道: t.me/szxglyhOneBot?startapp=glist 加群机器人: @szxglyhglBot

Channel
菲菲(05年幼师兼职)频道(🉑ks吻69)
@fefe977
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
512subscribers
+136 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 | -1004333551848 |
|---|---|
| Type | Channel |
| Username | @fefe977 |
| Created | Between 1 June 2026 and 22 September 2026 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 15 October 2026 |
| Last confirmed live | 30 October 2026 |
| Measurements held | 4 |
| Confirmed unchanged | 1 time, most recently 30 October 2026 |
| On Telegram | t.me/fefe977 |
Topic
Adult — a classification, not a measurement. An on-box language model (qwen3.6:35b-a3b, prompt version 1) read this channel’s own recent posts on 30 October 2026 and assigned it the closest of 31 fixed categories, at 64% 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 the other topics.
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 30 Oct 2026, 15:38 | 512 | +37 |
| 23 Oct 2026, 09:45 | 475 | +87 |
| 15 Oct 2026, 20:59 | 388 | +12 |
| 15 Oct 2026, 14:22 | 376 | first reading |
Engagement
20 posts held, back to 22 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
- 89.3%
- avg views ÷ 512 subscribers
- Avg views / post
- 457
- 15 posts measured
- Reaction rate
- 0.373%
- reactions ÷ views · ER floor
- Posts in window
- 17
- of 20 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 2 of 15 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 15 October 2026 |
|---|---|
| Posts held | 20 (22 September 2026 – 15 October 2026) |
| Views total | 6,859 |
| Reactions total | 6 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 15 Oct 2026, 14:22 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
- 32s
- Average length
- 8s
Measured directly from 4 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
10 reactions across 3 posts, in 2 distinct kinds. The most used accounts for 80.0% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 8 | 80.0% | |
| 👍 | 2 | 20.0% |
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 20 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 10 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 20 most recent posts we hold, published 22 September 2026 to 15 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
【深圳淘宝修车团报告】 https://telegram.me/xiuchegbdd 【老师花名】#菲菲 【联系方式】 @fefe977 【老师位置】#福田 【工兵留名】阿发 【验证时间】10.14 【修车费用】900 【颜值身材】9 【服务内容】同课表 【优点缺点】嫩妹,年轻05年的,逼紧 【出击体验】老师本人和照片一样漂亮,给了水费后就脱衣服洗澡,老师有陪洗,还有水中萧,洗完擦干后躺床上等老师服务,老师的口交比较舒服,一吸一吐小老弟就起来了,口了一会儿转过来69一段时间,感觉差不多了就戴套进入正题,老师的女上比较舒服,还可以看到老师漂亮的脸蛋,后面又用了传教士和后入各种姿势持续啪啪啪,老师的体力和配合度高,你想做什么姿势老师都能积极配合,最后选了传教士姿势顺利出水。 【综合评分】9.5 🎆温馨提示: 以上仅代表个人体验,不作为出击推荐,报告仅供参考! 报告提交: @szcjcj 报告提交条件:需要提供约课记录或付款记录…
菲菲(05年幼师兼职)频道(🉑ks吻69) pinned «【深圳淘宝修车团报告】 https://telegram.me/xiuchegbdd 【老师花名】#菲菲 【联系方式】@fefe988 【老师位置】#福田 【工兵留名】shit damn 【验证时间】10.12 【修车费用】900p 【颜值身材】满分 【服务内容】xcz,深喉,🐍,69,一应俱全,各种姿势 【优点缺点】全是优点,害羞了点不太会聊天 【出击体验】第二次出击菲菲了。这一次再见菲菲觉得,竟然有点可爱。人比照片好看多了。依旧是熟悉的小寒暄然后洗澡,水中箫,然后来到床上,舌吻抚摸品箫69。05年的…»
#福田菲菲 已在深圳研究协会上榜🕵♀ 榜单:@hjkko25 群组:https://t.me/bvcgzf588
位置多多欢迎骚扰👍👍
今天课位多多欢迎预留👍👍
【深圳淘宝修车团报告】 https://telegram.me/xiuchegbdd 【老师花名】#菲菲 【联系方式】@fefe988 【老师位置】#福田 【工兵留名】shit damn 【验证时间】10.12 【修车费用】900p 【颜值身材】满分 【服务内容】xcz,深喉,🐍,69,一应俱全,各种姿势 【优点缺点】全是优点,害羞了点不太会聊天 【出击体验】第二次出击菲菲了。这一次再见菲菲觉得,竟然有点可爱。人比照片好看多了。依旧是熟悉的小寒暄然后洗澡,水中箫,然后来到床上,舌吻抚摸品箫69。05年的妹子绝对是嫩妹了,很多嫩妹不太配合,甚至舔逼都太配合。我也不太会舔也不太喜欢,但菲菲的太漂亮了又没有味道,实在是好这口。而且她还舔得很有反应。然后依旧女上位起手。今天状态不错,菲菲在上面纵横驰骋到没劲儿了也还坚挺不射,中间我接吻吃奶停不下来。索性抱起菲菲,娇小可爱的菲菲满大厅火车便当巡游抽插,来到镜子前疯狂输出最终一泄如注。可惜了…
今天课位多多、欢迎预留👍
今天课位多多👍欢迎预留🉑🈷️
🈳🈳🈳
今晚还有位👍
位置多多欢迎预留
Showing the 12 most recent of 20 posts we hold for @fefe977. 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 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.
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 30 October 2026 — this entry's latest reading, not the date you are reading this.
“菲菲(05年幼师兼职)频道(🉑ks吻69)” (@fefe977), 512 subscribers as measured 30 October 2026. Telegram Register, tgregister.com/channel/fefe977.
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.