骚叫预警!!高颜值中学女老师的反差一面~人前高贵清冷的小姐姐被主人大开腿绑在沙发上狠狠蹂躏,邪恶的咸猪手各种把玩揉捏妹子的D罩杯豪乳,下面AV棒大力震动不停,反差婊子叫起来一浪比一浪高哇~ #国产群 #高颜值 #棒棒GC #浪叫

Channel
绳艺轩 SM/捆绑 调教室
@twelve_bondage
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Cite this entry
23,626subscribers
+20,928 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 | -1003880158746 |
|---|---|
| Type | Channel |
| Username | @twelve_bondage |
| Created | Between 1 February 2026 and 31 July 2026 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 31 October 2026 |
| Measurements held | 36 |
| Confirmed unchanged | 1 time, most recently 31 October 2026 |
| On Telegram | t.me/twelve_bondage |
Topic
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 12 September 2026 and assigned it the closest of 31 fixed categories, at 100% 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 |
|---|---|---|
| 31 Oct 2026, 05:26 | 23,626 | +314 |
| 30 Oct 2026, 03:18 | 23,312 | +305 |
| 29 Oct 2026, 05:17 | 23,007 | +353 |
| 28 Oct 2026, 00:16 | 22,654 | +332 |
| 27 Oct 2026, 00:25 | 22,322 | +268 |
| 26 Oct 2026, 00:06 | 22,054 | +289 |
| 25 Oct 2026, 00:16 | 21,765 | +315 |
| 24 Oct 2026, 02:11 | 21,450 | +325 |
| 23 Oct 2026, 00:57 | 21,125 | +291 |
| 22 Oct 2026, 02:17 | 20,834 | +280 |
| 20 Oct 2026, 20:39 | 20,554 | +209 |
| 19 Oct 2026, 21:06 | 20,345 | +301 |
| 18 Oct 2026, 18:27 | 20,044 | +245 |
| 17 Oct 2026, 20:06 | 19,799 | +342 |
| 16 Oct 2026, 20:18 | 19,457 | +293 |
| 15 Oct 2026, 23:10 | 19,164 | +297 |
| 14 Oct 2026, 22:48 | 18,867 | +534 |
| 13 Oct 2026, 13:58 | 18,333 | +1,499 |
| 9 Oct 2026, 12:15 | 16,834 | +1,515 |
| 5 Oct 2026, 05:41 | 15,319 | first reading |
Engagement
4 posts held, back to 7 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.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 4 posts for this entry, the most recent from 7 August 2026. An engagement rate over an empty window would be a number about nothing.
What this channel posts
- Video runtime
- 52m 34s
- Average length
- 13m 09s
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
1 reaction across 1 post, in 1 kind.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 1 | 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 1 of the 4 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 1 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 4 most recent posts we hold, published 7 August 2026 to 7 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
音量预警!!深夜酒店玩弄新约的反差大二小M,一进门就被主人脱得精光大开腿放置在床,强力AV棒+筋膜枪+炮机各种玩虐妹子的白虎小穴,狂暴抽插与高频震动下绝望的高潮不停,下面狂喷的白浆淫水弄得满地都是…… #无码群 #炮机 #道具GC #叫声可射
❤1
浪叫预警!!漫展偶然遇到的小coser调教后续,酒店k9犬缚跪地强令舔舐大号假阳具深喉play,沙发上大开腿固定放置,秒潮玩具+入体跳蛋内外联振飞骚货弄的高潮迭起淫叫不停 #国产群 #深喉 #秒潮 #浪叫呻吟
超高颜值~超反差~今年约到的颜值前三新妹子然然试绑,清纯外表下其实内心闷骚的很,一进门就自己脱到只剩内衣,情趣黑丝驷马放置挣扎不断,一边扭动一边呻吟娇喘越来越粗重…… #国产群 #超清纯 #黑丝 #放置挣扎
Showing the 4 most recent of 4 posts we hold for @twelve_bondage. 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.
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 31 October 2026 — this entry's latest reading, not the date you are reading this.
“绳艺轩 SM/捆绑 调教室” (@twelve_bondage), 23,626 subscribers as measured 31 October 2026. Telegram Register, tgregister.com/channel/twelve_bondage.
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.