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Telegram profile photo for 雯雯(思明区)👄

Channel

雯雯(思明区)👄

@mxgserta

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

170subscribers

+0 since we began measuring on 15 November 2026

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

Register entry

Telegram ID-1003896566323
TypeChannel
Username@mxgserta
Created12 November 2026 — measured — dated from the channel’s first post
First recorded15 November 2026
Last confirmed live15 November 2026
Measurements held2
On Telegramt.me/mxgserta

Growth

17015 Nov 2026, 11:47 — 170 subscribers15 Nov 2026, 12:22 — 170 subscribers15 Nov 2026, 11:4715 Nov 2026, 12:22
2 measurements taken within a single day. 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 169–171 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
15 Nov 2026, 12:22170no change
15 Nov 2026, 11:47170first reading

Engagement

5 posts held, back to 12 November 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
215.6%
avg views ÷ 170 subscribers
Avg views / post
367
4 posts measured
Reaction rate
0.331%
reactions ÷ views · ER floor
Posts in window
5
of 5 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 4 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 13 November 2026
Posts held5 (12 November 2026 – 13 November 2026)
Views total1,466
Reactions total3
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken15 Nov 2026, 12:22 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

Photos
6
Videos
1
Links
2

Lifetime counters from Telegram’s own channel header, read 15 November 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.

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

3 reactions across 2 posts, in 2 distinct kinds. The most used accounts for 66.7% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤266.7%
🤮133.3%

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 2 of the 5 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 5 most recent posts we hold, published 12 November 2026 to 13 November 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

Telegram’s own ‘edited’ marker: 0 of 5 posts held from the last 30 days (0%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).

12 Nov 2026, 13:07 UTC346 views2 reactionsread 15 November 2026
Forwarded from @Xiamen7777Photo

❤️萝卜青菜各有所爱,出击感受仅代表个人喜好以及观点,请各位自行斟酌考量❗️ 厦门工兵 报告模板 【出击日期】:11.12 【验证工兵】:(用户名) 【老师艺名】:雯雯 【老师账号】:@mebxrs(用户名) 【城市地区】:思明区 【水费次数】:p400 【人照相似】:90(满分100) 【目测年龄】:26 【颜值妆造】:90(满分100) 【身材曲线】:90(满分100) 【乳房状态】:D(大小/真假) 【臀部形态】:翘臀(小巧/大翘) 【皮肤状态】:光滑手感好(肤色/质感) 【bb的状态】:水多逼紧(户型/紧湿度) 【服务评分】:95(满分100) 【情绪价值】:96(满分100) 今天就想约个服务系老师放松一下,约了雯雯老师,服务是真的好,就单单一个口活加深喉都差点让我缴械投降了,女上不错、床上挺主动、情绪价值很足,态度很好,4张的价格能有这服务,还要什么自行车,喜欢的闭眼冲吧! 【日☀️后感 /详细描…

❤2

12 Nov 2026, 13:06 UTC331 viewsread 15 November 2026
Forwarded from @Xiamen7777Photo

❤️萝卜青菜各有所爱,出击感受仅代表个人喜好以及观点,请各位自行斟酌考量❗️ 厦门工兵 报告模板 【出击日期】:11.12 【验证工兵】:bobo 【老师艺名】:雯雯 【老师账号】:@mebxrs 【城市地区】:思明区 【水费次数】:p400 【人照相似】:90 【目测年龄】:26 【颜值妆造】:90 【身材曲线】:90 【乳房状态】:D 【臀部形态】:翘臀 【皮肤状态】:皮肤很好 【bb的状态】:水多逼紧 【服务评分】:96 【情绪价值】:98 【日☀️后感 /详细描述】: 今天出击的雯雯老师 ,服务是真的好,首先进门就让人眼前一亮 跟照片有个8 -9分像,我觉得比照片好看多了,老师说她不太上相,身材挺好的,大D胸,丰满有度,性感美女一个,态度超级好,跟女朋友一样,一会会就熟悉的跟一个人似的,性格超好,服务做的很好,我最喜欢老师给我口,那骚气的小表情,太吸引人了,直接一把拉过来床上戴套干起来,爽歪歪,有肉感后…

12 Nov 2026, 05:16 UTC559 views1 reactionsread 15 November 2026
Photo

用户名:@mebxrs 双向机器人:@sjxgshbsw_bot

🤮1

Showing the 5 most recent of 5 posts we hold for @mxgserta. 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 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 November 2026 — this entry's latest reading, not the date you are reading this.

“雯雯(思明区)👄” (@mxgserta), 170 subscribers as measured 15 November 2026. Telegram Register, tgregister.com/channel/mxgserta.

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.