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Channel
书墨资源
@shumozy
On this record: Growth · Engagement · Reactions · Posts · Citations · Handles named that no longer answer · Cite this entry
20,231subscribers
+155 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 10,000–31,623.
Register entry
| Telegram ID | -1001242245865 |
|---|---|
| Type | Channel |
| Username | @shumozy |
| Created | Between 1 March 2018 and 30 June 2021— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 14 August 2026 |
| Measurements held | 10 |
| Confirmed unchanged | 1 time, most recently 14 August 2026 |
| On Telegram | t.me/shumozy |
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 14 Aug 2026, 01:44 | 20,231 | +10 |
| 12 Aug 2026, 21:14 | 20,221 | +16 |
| 10 Aug 2026, 19:17 | 20,205 | +11 |
| 9 Aug 2026, 21:54 | 20,194 | +39 |
| 8 Aug 2026, 23:50 | 20,155 | +23 |
| 8 Aug 2026, 03:04 | 20,132 | +40 |
| 7 Aug 2026, 02:47 | 20,092 | +12 |
| 6 Aug 2026, 04:00 | 20,080 | +4 |
| 6 Aug 2026, 02:06 | 20,076 | no change |
| 6 Aug 2026, 01:53 | 20,076 | first reading |
Engagement
113 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 21 pagesof Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 1.34%
- avg views ÷ 20,231 subscribers
- Avg views / post
- 271
- 113 posts measured
- Reaction rate
- 0.416%
- reactions ÷ views · ER floor
- Posts in window
- 113
- of 113 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 18 of 113 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 13 August 2026 |
|---|---|
| Posts held | 113 (5 August 2026 – 13 August 2026) |
| Views total | 30,574 |
| Reactions total | 23 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 13 Aug 2026, 13:14 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
17 reactions across 11 posts, in 3 distinct kinds. The most used accounts for 58.8% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 10 | 58.8% | |
| 👍 | 6 | 35.3% | |
| 🔥 | 1 | 5.88% |
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 18 of the 113 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 23reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 113 most recent posts we hold, published 5 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.
Recent posts
斩神之凡尘神域 (2024) 4K S02全 简介:"若黯夜终临,吾必立于万万人前,横刀向渊,血染天穹!" 你是否想过,在霓虹璀璨的都市之下,潜藏着来自... 通过网盘分享的文件: 链接: https://pan.baidu.com/s/1F1wIAn8EZCtD6uVTjOACaA?pwd=j66f 频道指南 机场推荐 AI绘画
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天涯社区,优质书籍52本,天涯阅读量超五百万的精品合 📝 精选天涯社区阅读量超五百万的巅峰之作,涵盖历史秘闻、社会洞察、哲学思辨与离奇故事,汇聚全网最具深度和话题性的民间神帖,带你窥见文字背后的时代脉搏与人性真相。 https://pan.quark.cn/s/8565022abc41 #天涯 #神贴 #电子书 频道指南 机场推荐 AI绘画
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👍2
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九门 (2026) 4K 更新 E01 - 24 集 描述:长沙风云再起之时,张启山(陈伟霆 饰)与吴老狗(曾舜晞 饰)强强联手,携手霍仙姑(陈瑶 饰)与九门诸人共赴冒险奇局。一桩401部队的神秘失踪事件,牵出百年尘封的惊天秘辛。生死抉择、兄弟之情、门派担当与家国大义相互交织。九门众人用热血和牺牲,守护家园,共渡难关。 https://pan.baidu.com/s/1x_U25Fr5XOOmP0OZdu5Ltw?pwd=akxg 频道指南 机场推荐 AI绘画
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Showing the 12 most recent of 113 posts we hold for @shumozy. 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
Citation-graph rank — 65,694 of 1,189,255entries 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
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.
Mentions
Named by 35 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. The 24 listed below are the most frequent namers; the rest are counted above but not each listed.
Named by
Channels on the register whose posts name this channel's handle.
@CN_DH · 6,7618 posts优质信息收藏夹
@chunse1024 · 21,5486 posts副业赚钱探索指南
@text1024 · 16,5926 posts两性知识
@liangxing365 · 13,5604 posts出海🚢&自媒体运营秘籍
@yunying23 · 20,4184 posts电脑软件资源
@shumopc1 · 583 postsAI探索指南
@aigc1024 · 36,3492 postsAPPDO的互联网记忆
@appdopic · 15,7862 postsAppinn Feed|小众软件
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@dogdairy · 13,4102 posts超级索引🔍
@hao123hub · 1,0512 posts互联网从业者充电站
@https1024 · 29,9412 posts你不知道的内幕消息🅥
@inside1024 · 105,5802 posts夸克网盘资源俱乐部
@kkdj001 · 6,0992 posts你不知道的冷知识
@knowledge1024 · 19,0892 postsLIHAI 分享
@lihaiba · 38,7702 posts App Store 限免应用 & ...
@ooapps · 8,4492 posts安卓软件资源
@shumoandroid1 · 472 posts折腾啥
@zhetengsha · 47,4502 posts阿里云盘资源采集
@aliyunpanURL · 31 post大聪明 破解软件分享频道
@dcmpj · 38,4401 post🐾东萝东萝教教教🐾
@Loli_File · 9,3851 post115影视资源分享频道
@QukanMovie · 28,5951 post日更100 刺猬猫菠萝包起点飞卢小说有声书txt分享
@xkjdz55 · 18,7581 post
Names
Channels on the register whose handles appear in this channel's posts.
@aigc1024 · 36,3493 posts优质信息收藏夹
@chunse1024 · 21,5483 posts中年人生存报告
@dogdairy · 13,4103 posts互联网从业者充电站
@https1024 · 29,9413 posts你不知道的内幕消息🅥
@inside1024 · 105,5803 posts你不知道的冷知识
@knowledge1024 · 19,0893 posts两性知识
@liangxing365 · 13,5603 posts副业赚钱探索指南
@text1024 · 16,5923 posts出海🚢&自媒体运营秘籍
@yunying23 · 20,4183 posts🇩🇪德國精選生活素材
@delifex · 8362 postsGitHub 红队武器库🚨
@GithubRedTeam · 13,6672 posts黑洞加速VPN|官方频道
@heidongjiasu_Vpn01 · 4492 posts「 叙事诗 」影像与文字 ✨
@im_vlogs · 7442 posts极搜🔍中文搜索@JISO
@jiso · 292,5922 posts极搜🔍资源搜索@JISOU
@jisou · 5,546,0622 posts快搜🔍资源搜索@kuai
@kuaiaa · 1,380,5192 posts🌈乐趣驿站🎈
@lequyizhan · 42,2432 postsMK体育—飞投版: MK.BET
@MKFT777 · 2,6192 posts✨代理/高速节点/机场/加速器/VPN/免费分享
@nodespd · 9362 posts App Store 限免应用 & ...
@ooapps · 8,4492 posts东南亚资讯|聚焦
@rdsjo · 15,7002 posts🌈破解软件分享✨
@syrjfx_sl · 100,9632 posts台灣精選生活素材
@twlifex · 1,0682 postsVmeis | 唯美🍥
@Vmeis · 9952 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
- 2
- 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
- 2
- vacant every time we have ever looked
@shumozy named 2 handles 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 7 posts, 8 August 2026 – 13 August 2026
named in 2 posts, 10 August 2026 – 13 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 14 August 2026 — this entry's latest reading, not the date you are reading this.
“书墨资源” (@shumozy), 20,231 subscribers as measured 14 August 2026. Telegram Register, tgregister.com/channel/shumozy.
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.