#互推 【转存&引流】媒体托管机器人 【网络分享】纸鸢分享社-破解软件|游戏分享 【资源分享】浅秋分享社 | 破解软件 |游戏分享 【书籍小说】万卷书屋/小说推荐/禁忌书屋 【软件分享】大聪明 破解软件分享频道 【苹果限免】 App Store 限免应用 & ... 【机场测评】某咕咕的 机场 & VPN 测评站 【小说分享】音文拾光 🎵 精选小说音乐 分享推荐 【小说分享】爽文 | 穿越 |玄幻 | 涩文 | txt小说 Powered by @Summer_Clear_Sky_Bot

Channel
爽文 | 穿越 |玄幻 | 涩文 | txt小说
@gezhongxiaoshuo
On this record: Topic · Growth · Engagement · Reactions · Posts · Citations · Cite this entry
9,254subscribers
+1,534 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 3,162–10,000.
Register entry
| Telegram ID | -1003110499055 |
|---|---|
| Type | Channel |
| Username | @gezhongxiaoshuo |
| Created | Between 1 September 2025 and 30 November 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 17 September 2026 |
| Measurements held | 14 |
| Confirmed unchanged | 1 time, most recently 17 September 2026 |
| On Telegram | t.me/gezhongxiaoshuo |
Topic
Software piracy — 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 11 September 2026 and assigned it the closest of 31 fixed categories, at 69% 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.
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 17 Sept 2026, 04:58 | 9,254 | +204 |
| 12 Sept 2026, 22:40 | 9,050 | +203 |
| 8 Sept 2026, 14:35 | 8,847 | +128 |
| 3 Sept 2026, 17:57 | 8,719 | +86 |
| 31 Aug 2026, 13:26 | 8,633 | +174 |
| 28 Aug 2026, 13:36 | 8,459 | +73 |
| 25 Aug 2026, 13:27 | 8,386 | +94 |
| 22 Aug 2026, 14:14 | 8,292 | +70 |
| 19 Aug 2026, 09:47 | 8,222 | +42 |
| 16 Aug 2026, 20:14 | 8,180 | +102 |
| 13 Aug 2026, 01:35 | 8,078 | +101 |
| 9 Aug 2026, 16:01 | 7,977 | +233 |
| 7 Aug 2026, 00:38 | 7,744 | +24 |
| 6 Aug 2026, 06:47 | 7,720 | first reading |
Engagement
126 posts held, back to 2 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 31 pages of Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 6.45%
- avg views ÷ 9,254 subscribers
- Avg views / post
- 597
- 18 posts measured
- Reaction rate
- 0.077%
- reactions ÷ views · ER floor
- Posts in window
- 18
- of 126 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 18 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 28 August 2026 |
|---|---|
| Posts held | 126 (2 August 2026 – 28 August 2026) |
| Views total | 10,752 |
| Reactions total | 1 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 28 Aug 2026, 18:26 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.
Reaction mix
13 reactions across 11 posts, in 3 distinct kinds. The most used accounts for 76.9% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 10 | 76.9% | |
| 👎 | 2 | 15.4% | |
| 👍 | 1 | 7.69% |
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 126 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 13 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 126 most recent posts we hold, published 2 August 2026 to 28 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
搜小说、搜资源,来这里找找看吧,包你满意 👇👇 https://t.me/+aGLyi0kvkK1hYTYx
《灰衣奴》作者:彻夜流香 雪中施粥的一次收留,让哑巴小乞丐将小王爷亦非刻进心底。多年后,他已是金陵才子陈清秋,却甘愿毁容披灰衣、重返王府为奴,只为靠近那个早已不记得自己的人;二十年痴守,近在咫尺却如隔天涯。 #古代 #BL #主仆 #虐恋
❤1
🔞《强制配对生育条例》作者:由夏 未来人口负增长,双性人数稀缺,联合会议颁布强制受孕与社会服务法案。保守学生宋朝歌在法案生效首日便被卷入贞操危机,在制度压迫与欲望纠葛中挣扎;精神1v1,肉体NP,结局1v1。 #BL #未来 #双性 #涩文
Telegram必备的搜索引擎,极搜JISOU帮你精准找到,想要的群组、频道、视频、音乐 👉 t.me/jisou2?start=a_5263232871
🔞《掌控人生》作者:难受住了 雨夜遭掳的虞焕醒来便身陷地下囚室,被神秘施虐者以残忍手段掌控、调教与改造。昔日骄纵少年逐渐身心崩溃,沦为无法逃离的禁脔;主打暗黑囚禁、强制虐身与重口痛肉。 #BL #暗黑 #囚禁 #涩文
《帅哥邻居求着要做我的狗》作者:焆星星 母胎单身的颜色文作者安穗,为找灵感盯上高冷帅气的新邻居时清让。谁知嫌她满脑子废料的高岭之花先动了心,从嘴硬避嫌到主动低头:“安穗,我给你做狗?”邻居互撩,甜虐拉扯,狐狸终被小狗拿下。 #现代 #甜宠 #欢喜冤家 #邻居
🔞《直男也能给人当老婆吗》作者:陆酌言 恐同直男误会竹马的暗恋后冲动绝交,失去才知后悔。为追回冷淡竹马,他竟主动提出“给你当老婆”!从嘴硬直男到缺爱黏人精,青梅竹马暗恋成真,酸甜狗血又走心走肾。 #BL #青梅竹马 #直掰弯 #涩文
《少爷别骂了我真跳了》作者:朝朝不是找找 徐若缇穿成古早虐文炮灰,面对家暴父母、绿茶弟弟与渣未婚夫,直接摆烂开怼,连系统任务也不想做。偏偏弟弟的高岭之花官配戚别俞被他吸引,误会越滚越大,好感度一路失控。 #穿书 #系统 #豪门 #欢喜冤家
《仙君踏月而来》作者:楚执 宋悯欢穿进虐师修仙文,成了男主师兄,决心救下会被凌辱惨死的温柔仙君师尊,也阻止美强惨师弟黑化。原著命运逐渐偏离,师弟与仙君却都对他生出异样执念,三人关系暗流涌动。 #穿书 #修真 #师徒 #救赎
《隔壁的小书生》作者:少地瓜 桃花镇的穷书生为省钱日日做饭,意外被路过女侠盯上砂锅粥。一个安静温吞,一个爽朗洒脱,两颗孤独的心在家常饭菜与小镇烟火里慢慢靠近、彼此治愈。 #种田 #美食 #江湖 #治愈
《血族少女爱上我》作者:机巧少女不会233 哥哥意外换上妹妹的衣裙,卷入血族少女们热烈又混乱的青春日常。主打无敌设定、萌系少女与轻松恋爱喜剧,在身份错位和少女情愫中展开高甜故事。 #变百 #血族 #校园 #甜宠
Showing the 12 most recent of 126 posts we hold for @gezhongxiaoshuo. 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.
Mentions
Named by 19 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.
Named by
Channels on the register whose posts name this channel's handle.
@AChansp · 23,5743 posts便宜机场测速
@cheap_proxy · 25,8233 posts公诸同好 | 二次元美图分享 🅥
@gongzhutonghao · 37,9923 posts115影视资源分享频道
@QukanMovie · 30,5353 posts万卷书屋/小说推荐/禁忌书屋
@wanjsw · 220,2273 postsAPPDO的互联网记忆
@appdopic · 16,1922 posts大聪明 破解软件分享频道
@dcmpj · 41,4982 posts飞鱼资源分享|冲浪指南|软件工具
@feiyu123 · 61,8562 postsLIHAI 分享
@lihaiba · 39,1352 posts App Store 限免应用 & ...
@ooapps · 9,9102 posts浅秋分享社 | 破解软件 |游戏分享
@QQFXS · 45,6252 posts书墨资源
@shumozy · 20,7692 postsAppinn Feed|小众软件
@appinnfeed · 33,3611 post来一点医学科学前沿🤯🤯🥹🥹
@CNSmydream · 13,2931 post🐾东萝东萝教教教🐾
@Loli_File · 10,5461 post小声逼逼
@me888888888888 · 50,3291 post朱颜别镜 | 妹子图 | 美女图
@meizitu3 · 49,7681 post折腾啥
@zhetengsha · 49,2691 post纸鸢分享社-破解软件|游戏分享
@zhiyuanfxs · 87,2871 post
Names
Channels on the register whose handles appear in this channel's posts.
@jisou2 · 1,747,98010 posts永不消逝的音声
@ASMR86866 · 26,2433 posts频道索引&推荐
@recommend3 · 106,8493 postsNaruto 频道推荐 👍👍👍
@AChansp · 23,5742 posts音文拾光 🎵 精选小说音乐 分享推荐
@Flymirai · 24,3732 posts公诸同好 | 二次元美图分享 🅥
@gongzhutonghao · 37,9922 posts App Store 限免应用 & ...
@ooapps · 9,9102 posts115影视资源分享频道
@QukanMovie · 30,5352 posts书墨资源
@shumozy · 20,7692 posts万卷书屋/小说推荐/禁忌书屋
@wanjsw · 220,2272 postsAPPDO的互联网记忆
@appdopic · 16,1921 post便宜机场测速
@cheap_proxy · 25,8231 post来一点医学科学前沿🤯🤯🥹🥹
@CNSmydream · 13,2931 post大聪明 破解软件分享频道
@dcmpj · 41,4981 postFFQ Cloud 订阅|id分享中心
@ffqidfx · 6,8681 post电子书资源分享 📚
@KaiPanshare · 16,9121 post🐾东萝东萝教教教🐾
@Loli_File · 10,5461 post某咕咕的 机场 & VPN 测评站
@MiaoMiaoGuGa · 8,6071 post浅秋分享社 | 破解软件 |游戏分享
@QQFXS · 45,6251 post一个普通的壁纸频道喵~
@thomasdadw · 2,8891 postTK集库
@tkjiku · 24,6471 post观影视界[GyWEB]
@WFYSFX03 · 6,5941 post纸鸢分享社-破解软件|游戏分享
@zhiyuanfxs · 87,2871 post资源分享客栈-Applnn
@zyfxlnn · 32,4691 post
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 17 September 2026 — this entry's latest reading, not the date you are reading this.
“爽文 | 穿越 |玄幻 | 涩文 | txt小说” (@gezhongxiaoshuo), 9,254 subscribers as measured 17 September 2026. Telegram Register, tgregister.com/channel/gezhongxiaoshuo.
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.