😀😀😀😀😀😀😀😀 #《jojo熟女合集》 推特大神的资源合集:来个熟女大混剪吧,感觉熟了点,但是群里会有粉丝会喜欢的 (登录官网尽享超清) 关键词:#西瓜短剧 #AI短剧 #jojo熟女合集
❤18👍2

Channel
@xgduanju
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Handles named that no longer answer · Cite this entry
166,310subscribers
+11,070 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 100,000–316,228.
| Telegram ID | -1002533442302 |
|---|---|
| Type | Channel |
| Username | @xgduanju |
| Created | Between 1 March 2025 and 31 July 2025— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 15 August 2026 |
| Measurements held | 9 |
| Confirmed unchanged | 1 time, most recently 15 August 2026 |
| On Telegram | t.me/xgduanju |
Adult — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 8 August 2026 and assigned it the closest of 31 fixed categories, at 62% 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 why it has no browse page of its own yet.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 15 Aug 2026, 07:54 | 166,310 | -1,935 |
| 14 Aug 2026, 02:35 | 168,245 | +1,746 |
| 12 Aug 2026, 23:23 | 166,499 | +2,574 |
| 11 Aug 2026, 20:31 | 163,925 | +2,940 |
| 10 Aug 2026, 19:51 | 160,985 | +1,965 |
| 9 Aug 2026, 20:52 | 159,020 | +1,119 |
| 8 Aug 2026, 23:38 | 157,901 | +1,299 |
| 7 Aug 2026, 21:22 | 156,602 | +1,362 |
| 6 Aug 2026, 22:16 | 155,240 | first reading |
46 posts held, back to 4 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 19 pagesof Telegram’s post history, 20 posts per page.
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.
| Window | Rolling 30 days · latest post in window 13 August 2026 |
|---|---|
| Posts held | 46 (4 August 2026 – 13 August 2026) |
| Views total | 1,800,800 |
| Reactions total | 2,260 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 13 Aug 2026, 18:27 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.
Measured directly from 39 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.
2,260 reactions across 46 posts, in 17 distinct kinds. The most used accounts for 80.4% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 1,817 | 80.4% | |
| 💩 | 172 | 7.61% | |
| 👍 | 70 | 3.10% | |
| 🤣 | 37 | 1.64% | |
| 🥰 | 35 | 1.55% | |
| 🔥 | 31 | 1.37% | |
| 👏 | 24 | 1.06% | |
| 🆒 | 20 | 0.885% | |
| 🤯 | 15 | 0.664% | |
| 🤮 | 14 | 0.619% | |
| 🤡 | 8 | 0.354% | |
| 😁 | 6 | 0.265% | |
| 🐳 | 4 | 0.177% | |
| 👎 | 4 | 0.177% | |
| 🌭 | 1 | 0.044% | |
| 🙏 | 1 | 0.044% | |
| 🤩 | 1 | 0.044% |
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 46 of the 46 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 2,260reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 46 most recent posts we hold, published 4 August 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.
😀😀😀😀😀😀😀😀 #《jojo熟女合集》 推特大神的资源合集:来个熟女大混剪吧,感觉熟了点,但是群里会有粉丝会喜欢的 (登录官网尽享超清) 关键词:#西瓜短剧 #AI短剧 #jojo熟女合集
❤18👍2
😀😀😀😀😀😀😀😀 #《古寺艳鬼录》EP-8 夜伴灵姬的无码版本,魔改失去了原版的味道,后面越来越短 (登录官网尽享超清) 关键词:#西瓜短剧 #AI短剧 #古寺艳鬼录
❤19
😀😀😀😀😀😀😀😀 #《Bin大小姐元宇宙》 EP 1-9 最终还是进军了影视圈,我的Bingege,当太阳升起时,就把昨天忘掉 (登录官网尽享超清) 关键词:#西瓜短剧 #AI短剧 #Bin大小姐元宇宙
❤18🤯15🐳1
😀😀😀😀😀😀😀😀 #《牛郎的牛牛很牛》 最近没有什么特别好的单体作品,还是这种无水印,真实反差的观感好一点 (登录官网尽享超清) 关键词:#西瓜短剧 #AI短剧 #牛郎的牛牛很牛
❤11🙏1
😀😀😀😀😀😀😀😀 #《潜入女生宿舍》EP-3 不科学,为什么连宿管阿姨都没有的,后剧情应该是要把宿管阿姨一起拿下才对啊,剧本不行 (登录官网尽享超清) 关键词:#西瓜短剧 #AI短剧 #潜入女生宿舍
❤61
😀😀😀😀😀😀😀😀 #《神瞳觉醒》EP-11 多的不解释,伦理+熟女,看就完事了,不知道会有继续更新的 (登录官网尽享超清) 关键词:#西瓜短剧 #AI短剧 #神瞳觉醒
❤47🔥1
😀😀😀😀😀😀😀😀 #《南山古宅的倩影》 EP1-3 这个作者比较擅长隔空点穴,但是这部确实不错啊,有惊悚的感觉 (登录官网尽享超清) 关键词:#西瓜短剧 #AI短剧 #南山古宅的倩影
❤22💩4😁2👍1👏1🥰1
😀😀😀😀😀😀😀😀 #《我和僵尸有个约会》 最近没有什么特别好的单体作品,还是这种无水印,真实反差的观感好一点 (登录官网尽享超清) 关键词:#西瓜短剧 #AI短剧 #我和僵尸有个约会
❤29💩19
😀😀😀😀😀😀😀😀 #《患性瘾的巨乳女教师》EP-2 模型有点像百万大奖赛里面的妈妈了,有点意思 (登录官网尽享超清) 关键词:#西瓜短剧 #AI短剧 #患性瘾的巨乳女教师
❤27💩9👍1👎1🔥1
😀😀😀😀😀😀😀😀 #《96岁快死的老头觉醒系统,第二天直接返老还童》EP-35 王建强。 96岁。 合欢宗外门老头。 废灵根。 没背景。 没天赋。 活了一辈子都被人瞧不起。 所有人都觉得。 他离死不远了。 就连亲侄女上门。 也只是为了骗走他最后的丹药。 可就在濒死之际。 系统觉醒! 超神修炼系统已激活!。 (登录官网尽享超清) 关键词:#西瓜短剧 #AI短剧 #长生录从侄女上门求丹开始长生
❤23💩6👍1
😀😀😀😀😀😀😀😀 #《甄嬛传:禁苑情劫》 EP 1-6 没啥特别好的资源,心动传媒的作品一般都还可以,我这个网盘资源水印有点多,随意看了。代入原本IP进去还可以的 (登录官网尽享超清) 关键词:#西瓜短剧 #AI短剧 #甄嬛传
❤45👏10🐳3🔥2👍1
😀😀😀😀😀😀😀😀 #《现代都市丽人》 EP 1-10 网盘大佬自制漫改AI短剧,人物剧情都很还原,先同步了,这个我感觉不错,原创作者:@WengYin5 (登录官网尽享超清) 关键词:#西瓜短剧 #AI短剧 #现代都市丽人
❤69🔥5💩3
Showing the 12 most recent of 46 posts we hold for @xgduanju. 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.
Citation-graph rank — 309,745 of 1,481,243entries 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.
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
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.
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.
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.
@xgduanju 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.
References a handle that is not a live channel — we have no record it ever was one.
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 August 2026 — this entry's latest reading, not the date you are reading this.
“西瓜短剧(AI短剧)” (@xgduanju), 166,310 subscribers as measured 15 August 2026. Telegram Register, tgregister.com/channel/xgduanju.
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.