⭐⭐ 🤓🤓 【新茶推薦】編號:絮寧 地點:#台北 ━━━━━━━━━━━━━━ 🎓 學歷:20歲 | #輔仁大學(氣質學生系) 🔔 檔案:159cm / 44kg / C罩杯 🔔 風格:個性自然、講話直接、學生氣很重 🔔 服務:好溝通、不趕時間、互動不冷場 ⏰ 狀態:🟢 【今日時間彈性,可先詢問】 ━━━━━━━━━━━━━━ ❤️簡介:課餘想自己多存點生活費,沒什麼複雜社會經驗,熟起來反而很會聊!

Channel
全台清純學生妹總部
@ky6963
On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Posts edited after publishing · Citations · Handles named that no longer answer · Cite this entry
17,261subscribers
+16 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 | -1001930328708 |
|---|---|
| Type | Channel |
| Username | @ky6963 |
| Created | Between 1 April 2023 and 31 October 2023— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 30 August 2026 |
| Measurements held | 22 |
| Confirmed unchanged | 1 time, most recently 30 August 2026 |
| On Telegram | t.me/ky6963 |
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 30 Aug 2026, 23:42 | 17,261 | +1 |
| 30 Aug 2026, 01:54 | 17,260 | -1 |
| 29 Aug 2026, 02:49 | 17,261 | +2 |
| 28 Aug 2026, 01:54 | 17,259 | -2 |
| 27 Aug 2026, 03:34 | 17,261 | +4 |
| 26 Aug 2026, 04:18 | 17,257 | +1 |
| 24 Aug 2026, 08:12 | 17,256 | -1 |
| 22 Aug 2026, 15:28 | 17,257 | +5 |
| 21 Aug 2026, 07:33 | 17,252 | +2 |
| 20 Aug 2026, 10:54 | 17,250 | -2 |
| 19 Aug 2026, 13:15 | 17,252 | +2 |
| 18 Aug 2026, 16:35 | 17,250 | -3 |
| 17 Aug 2026, 16:57 | 17,253 | +1 |
| 16 Aug 2026, 14:58 | 17,252 | +2 |
| 14 Aug 2026, 20:08 | 17,250 | +1 |
| 13 Aug 2026, 13:05 | 17,249 | +3 |
| 11 Aug 2026, 11:04 | 17,246 | -1 |
| 10 Aug 2026, 09:01 | 17,247 | -3 |
| 9 Aug 2026, 05:56 | 17,250 | +2 |
| 8 Aug 2026, 07:44 | 17,248 | first reading |
Engagement
94 posts held, back to 5 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 41 pagesof Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 0.656%
- avg views ÷ 17,261 subscribers
- Avg views / post
- 113
- 94 posts measured
- Reaction rate
- 0.804%
- reactions ÷ views · ER floor
- Posts in window
- 94
- of 94 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 16 of 94 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 26 August 2026 |
|---|---|
| Posts held | 94 (5 August 2026 – 26 August 2026) |
| Views total | 10,649 |
| Reactions total | 18 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 27 Aug 2026, 12:19 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 25s
- Average length
- 36s
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
18 reactions across 16 posts, in 3 distinct kinds. The most used accounts for 83.3% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 15 | 83.3% | |
| 🔥 | 2 | 11.1% | |
| 👍 | 1 | 5.56% |
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 16 of the 94 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 18reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 94 most recent posts we hold, published 5 August 2026 to 26 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
【新茶推薦】芊芊 #新北新莊區 🎓 160cm 46kg C 21歲 #輔仁大學 3+1 60000 ⚡️ 謝謝熟客哥哥再次支持,也謝謝結束後還認真回來分享感受🤣 原本以為只是普通見面,結果3+1一路聊到開始互爆黑歷史 能讓平常話不多的熟客自己說「這個安排得不錯」,芊芊今天很可以~
⭐⭐🤓🤓 #台中 · #亞洲大學 😀朵寧 157 · 43 · C · 20歲 〔短髮妹妹〕〔講話很有梗〕 〔做事乾脆不拖〕〔熟了之後很會聊〕 #本日精選
⭐⭐🤓🤓 #台北 · #實踐大學 😀舒澄 161 · 43 · C · 20歲 〔暑假想存點零用錢〕〔不喝酒局〕 〔時間觀念很好〕〔講話不會裝熟〕 #本日精選
⭐⭐🤓🤓 #高雄 · #文藻外語大學 ⚡️吳優 156 · 40 · B · 19歲 〔第一次兼職〕〔學生感很重〕 〔生活圈單純〕〔個性比較慢熟〕 #本日精選
❤1
Video, posted without a caption
Video, posted without a caption
璐兒 160・45・C・19歲 嬌小可愛的小隻馬,青春感十足 喜歡後入 讓你欣賞流滿淫水的騷穴
⭐⭐🤓🤓 #高雄 · #文藻外語大學 ♡ 璟妍 162 · 45 · C · 21歲 〔生活圈單純〕〔沒什麼職場氣〕 〔個性直率〕〔聊天不太有距離感〕 #本日精選
⭐⭐🤓🤓 #台北 #銘傳大學 予安 · 158 · 45 · C.20歲 學生妹真的都喜歡年紀大一點的男生嗎?
#台中 · #靜宜大學 💕允希 160 · 46 · C · 20歲 〔生活圈單純〕〔學生感很重〕 〔個性直率〕〔熟了很有話聊〕 #本日精選 ━━━━━━━━━━━━━━
❤1
୨୧ 今日新面孔 · #台北 ୨୧ ━━━━━━━━━━━━━━ 🌸 采霏 161 · 46 · D · 21歲 #世新大學 ✦ 學生亮點 生活圈單純 · 沒什麼職場氣 個性比較直 · 聊熟後話很多 📱line:simple239 📱TG: @kkyy696 ❤️Gleezy: zy2162 🔞爆浆频道:@binglang0000 🩷選妹論壇:@twjiajia33.com 😀巨乳肥臀坦克社 :@ky6996 😀清純學生妹總部:@ky6963
Showing the 12 most recent of 94 posts we hold for @ky6963. 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
@ky6963 edited 2 posts 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
- 23 August 2026
Citation-graph rank
Citation-graph rank — 987,733 of 1,627,445entries 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 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.
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.
Handles this channel named that no longer answer
- Dead references
- 1
- handles named in this channel’s posts, vacant today
- Evidenced gone
- 0
- we ourselves saw one of these resolve, at some point
- Never seen alive
- 1
- vacant every time we have ever looked
@ky6963 named 1 handle that resolve to nothing today. That is a fact about the reference, not necessarily a fact about the handle’s history — see the two groups below.
Most of these may never have existed as a live channel at all.A handle a channel names can be a typo, an aspirational name nobody registered, or a channel that was already gone before this one ever mentioned it. Unless a row below is marked evidenced, all we know is that it references a handle that is not a live channel today — not that anything “died”. How this is measured.
Never seen alive
References a handle that is not a live channel — we have no record it ever was one.
named in 10 posts, 8 August 2026 – 21 August 2026
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 August 2026 — this entry's latest reading, not the date you are reading this.
“全台清純學生妹總部” (@ky6963), 17,261 subscribers as measured 30 August 2026. Telegram Register, tgregister.com/channel/ky6963.
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.