Telegram RegisterThe public register of Telegram

Channel

静宜的频道

@wan_dao

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

12,650subscribers

+7,126 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 10,000–31,623.

Register entry

Telegram ID-1003742828922
TypeChannel
Username@wan_dao
CreatedBetween 1 February 2026 and 30 June 2026— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live13 August 2026
Measurements held5
Confirmed unchanged1 time, most recently 13 August 2026
On Telegramt.me/wan_dao

Growth

5,52012,6509,0857 August 2026 — 5,524 subscribers8 August 2026 — 5,520 subscribers11 August 2026 — 11,755 subscribers12 August 2026 — 12,173 subscribers13 August 2026 — 12,650 subscribers7 August 202613 August 2026
5 measurements spanning 6 days, net +7,126. 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 4,451–13,720 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
13 Aug 2026, 11:2812,650+477
12 Aug 2026, 11:4312,173+418
11 Aug 2026, 11:2511,755+6,235
8 Aug 2026, 08:515,520-4
7 Aug 2026, 19:325,524first reading

Engagement

37 posts held, back to 9 July 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 10 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
3.83%
avg views ÷ 12,650 subscribers
Avg views / post
485
32 posts measured
Reaction rate
0.298%
reactions ÷ views · ER floor
Posts in window
35
of 37 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 6 of 32 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 August 2026
Posts held37 (9 July 202613 August 2026)
Views total15,510
Reactions total8
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken13 Aug 2026, 03:37 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
2m 04s
Average length
25s

Measured directly from 5 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

11 reactions across 7 posts, in 2 distinct kinds. The most used accounts for 90.9% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
1090.9%
👍19.09%

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 8 of the 37 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 11reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 37 most recent posts we hold, published 9 July 2026 to 13 August 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

13 Aug 2026, 03:24 UTC12 viewsread 13 August 2026
Photo

💐💐💐开奖了💐💐💐 南山御姐静宜:@dxm456 回馈狼友福利抽奖活动 开奖了! 本期总参与人数: 7303 1- 愿阳光炽热 获得:18.88奶茶红包 2- 裸奔的青春 获得:P100优惠券 3- 大湾仔 获得:P100优惠券 4- 清欢 获得:P100优惠券 5- Nina 获得:P100优惠券 6- 淡化 获得:P100优惠券 7- 净是缘由 获得:P100优惠券 8- 初遇未遇 获得:PP200优惠券 9- 人生就像秋千 获得:PP200优惠券 10- 怪你过份美丽 获得:PP200优惠券 11- 撩妹小能手 获得:PP200优惠券 12- 只因年轻 获得:PP200优惠券 13- 杀之恋 获得:PP200优惠券 14- 流浪忘带酒 获得:夜课500优惠券 15- 叽里咕噜🫧 获得:夜课500优惠券 16- 仓原图 获得:夜课500优惠券 17- 开大大大 获得:夜课500优惠券 1

12 Aug 2026, 22:04 UTC103 viewsread 13 August 2026
Video

🎁 南山区静宜口令红包¥500元:@dxm456 📦 奖品内容: 💰 口令红包¥500元 ×1 💰 P优惠100 ×3 💰 PP优惠200 ×3 💰 优惠500限包天与夜课 ×3 👥 参与条件: 🔗 加入-🏪深圳同城出击大队🏪 └ 💬 发言数大于 8 条 🔗 加入-🏪深圳同城优选榜🏪 🔗 加入-🏪同城报告发布🏪 🔗 加入-静宜的频道 ⏰ 开奖方式: 定时开奖: 2026年08月13日 12时00分00秒 ⚠️ 抽奖说明: 中奖者找当前管理员领取口令红包 优惠券找当前老师消费抵扣

10 Aug 2026, 11:14 UTC445 views2 reactionsread 13 August 2026
Photo

🎰 南山静宜活动 📮 参与条件: 🎫 加入-静宜的频道 🎫 加入-深圳嫩妹茶探府【导航群】 🎫 加入-深圳嫩妹茶探府【轮播群】 🎫 加入-深圳嫩妹茶探府 🎫 加入-深圳嫩妹茶探府【修车榜单】 🎫 加入-深圳嫩妹茶探府【出击报告】 🎁 奖品内容: 💰️ 18.88口令红包 × 1 💰️ 500优惠券限包天夜课 × 6 💰️ PP优惠200 × 6 💰️ P优惠100 × 6 ⚠️ 抽奖说明: 福利频道 https://t.me/+z28IyH8Sp_dmNzA1 🔋 人品加成:⚡️× 9 规则 📅 开奖日期:(北京时间) 2026年08月13日 12时13分00秒

2

9 Aug 2026, 18:26 UTC424 viewsread 13 August 2026

深圳南山区🌹🌹课表看顶置第一条 上课联系: @dxm456 双向联系: @tjyss678bot 爱爱AV 静宜福利聊天群:https://t.me/ttkxjingyi/6 ❤️静宜福利聊天群先加入静宜频道便可加入 自己聊无中介,没有回信息就是在忙,闲时第一时间回消息。

9 Aug 2026, 18:09 UTC379 views1 reactionsread 13 August 2026
Photo

20号🈵🈵🈵,有豪哥包天了可以约其他时间

1

9 Aug 2026, 18:02 UTC341 viewsread 13 August 2026
Video

胆子够肥在台风暴雨中怕视频宝宝们不得夸夸我吗😂😂

9 Aug 2026, 17:55 UTC344 views0 reactionsread 13 August 2026
Photo

西湖美景宝宝我们一起欣赏😘😘

8 Aug 2026, 16:17 UTCviews —

静宜的频道 pinned «👉积木(中文圈)@jimu 👉更多抽奖:@zhongwenquan 🎟️ 抽奖标题:南山 静宜 @dxm456 🎁 奖品内容: 💰️ 18.88口令红包🧧 × 1 💰️ p100优惠券 × 6 💰️ pp200优惠券 × 6 💰️ 包天/夜课500优惠券 × 6 🪧 抽奖说明:进学生群签到就可以兑换优惠券,全场通用!不用水群!人人都可以领到 -------------------------- -修车导航 - @szfenglinwan -中奖者请联系老师领奖 -优惠券有效期(十五天) ---------…»

8 Aug 2026, 16:17 UTC504 viewsread 12 August 2026

👉积木(中文圈)@jimu 👉更多抽奖:@zhongwenquan 🎟️ 抽奖标题:南山 静宜 @dxm456 🎁 奖品内容: 💰️ 18.88口令红包🧧 × 1 💰️ p100优惠券 × 6 💰️ pp200优惠券 × 6 💰️ 包天/夜课500优惠券 × 6 🪧 抽奖说明:进学生群签到就可以兑换优惠券,全场通用!不用水群!人人都可以领到 -------------------------- -修车导航 - @szfenglinwan -中奖者请联系老师领奖 -优惠券有效期(十五天) -------------------------- 🎫 参与条件: 🎫 加入 - 静宜的频道 🎫 加入 - 深圳枫林报告 @szflw 🎫 加入 - 深圳枫林晚优惠福利🧧 📅 开奖时间:2026-08-13T14:00自动开奖 🧱 开奖方式:比特币区块链可验证(公开透明) ⚠️:开奖前请勿删除抽奖信息(删除即抽奖失效) 👉 参与抽奖名单:ht

Showing the 12 most recent of 37 posts we hold for @wan_dao. 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.

Posts edited after publishing

@wan_dao edited 1 post after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.

An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.

First edit seen
8 August 2026
Most recent edit
12 August 2026

Citation-graph rank

Citation-graph rank — 125,567 of 1,169,250entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.

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 15 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 13 August 2026 — this entry's latest reading, not the date you are reading this.

“静宜的频道” (@wan_dao), 12,650 subscribers as measured 13 August 2026. Telegram Register, tgregister.com/channel/wan_dao.

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.