我早就不是技能单一程序员,我只是感概那些能花的时间😢 还有我要放弃编程,投入混沌的领域,比如说做社交媒体 这个年代,不确定性才是壁垒。能被系统规划的终究被 AI 吃掉。 优质「内容」 | 优质「资源」 | 你不知道的内幕消息🌳
Channel
优质信息收藏夹
@chunse1024
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Posts recorded as deleted · Citations · Handles named that no longer answer · Cite this entry
28,732subscribers
+7,452 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 | -1001854596532 |
|---|---|
| Type | Channel |
| Username | @chunse1024 |
| Created | Between 1 October 2022 and 30 September 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 12 November 2026 |
| Measurements held | 66 |
| Confirmed unchanged | 1 time, most recently 12 November 2026 |
| On Telegram | t.me/chunse1024 |
Topic
Technology — 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 10 September 2026 and assigned it the closest of 31 fixed categories, at 88% 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 |
|---|---|---|
| 12 Nov 2026, 13:05 | 28,732 | +40 |
| 10 Nov 2026, 09:27 | 28,692 | +60 |
| 8 Nov 2026, 20:56 | 28,632 | +28 |
| 7 Nov 2026, 15:05 | 28,604 | +62 |
| 6 Nov 2026, 17:17 | 28,542 | +25 |
| 5 Nov 2026, 20:41 | 28,517 | +66 |
| 4 Nov 2026, 21:00 | 28,451 | +30 |
| 3 Nov 2026, 21:35 | 28,421 | +325 |
| 2 Nov 2026, 17:48 | 28,096 | +510 |
| 1 Nov 2026, 16:58 | 27,586 | +30 |
| 31 Oct 2026, 19:27 | 27,556 | +9 |
| 30 Oct 2026, 20:49 | 27,547 | +18 |
| 29 Oct 2026, 19:58 | 27,529 | +36 |
| 28 Oct 2026, 20:11 | 27,493 | +43 |
| 27 Oct 2026, 19:08 | 27,450 | +27 |
| 26 Oct 2026, 20:17 | 27,423 | +25 |
| 25 Oct 2026, 19:55 | 27,398 | +45 |
| 24 Oct 2026, 19:08 | 27,353 | +14 |
| 23 Oct 2026, 21:34 | 27,339 | +32 |
| 22 Oct 2026, 18:18 | 27,307 | first reading |
Engagement
612 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 167 pages of Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 4.24%
- avg views ÷ 28,732 subscribers
- Avg views / post
- 1,220
- 229 posts measured
- Reaction rate
- 0.158%
- reactions ÷ views · ER floor
- Posts in window
- 229
- of 612 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 153 of 229 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 12 November 2026 |
|---|---|
| Posts held | 612 (2 August 2026 – 12 November 2026) |
| Views total | 279,239 |
| Reactions total | 321 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 12 Nov 2026, 10:49 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
- 1h 15m
- Average length
- 1m 05s
Measured directly from 69 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
724 reactions across 292 posts, in 22 distinct kinds. The most used accounts for 44.5% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 322 | 44.5% | |
| 👍 | 229 | 31.6% | |
| 🤡 | 36 | 4.97% | |
| 👀 | 28 | 3.87% | |
| 👎 | 24 | 3.31% | |
| 💩 | 16 | 2.21% | |
| 🤔 | 11 | 1.52% | |
| 🥴 | 11 | 1.52% | |
| 🌚 | 9 | 1.24% | |
| 😁 | 9 | 1.24% | |
| 👏 | 7 | 0.967% | |
| 😢 | 3 | 0.414% | |
| 🤩 | 3 | 0.414% | |
| 🤮 | 3 | 0.414% | |
| 🔥 | 2 | 0.276% | |
| 😱 | 2 | 0.276% | |
| 🤬 | 2 | 0.276% | |
| 🥰 | 2 | 0.276% | |
| 🫡 | 2 | 0.276% | |
| 🖕 | 1 | 0.138% | |
| 2 further kinds | 2 | 0.276% |
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 342 of the 612 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 731 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 612 most recent posts we hold, published 2 August 2026 to 12 November 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
Telegram’s own ‘edited’ marker: 0 of 229 posts held from the last 30 days (0%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).
《男人装》2010-2024年合集每期都是视觉盛宴。 https://pan.quark.cn/s/b39c8d18ca53 ———— 盘友资源库:https://pan.tgshangtian.xyz 优质资源 | 优质内容
❤1
Anna's Archive(安娜档案)是一个全球最大的开放性电子图书馆整合平台,集合了LibGen(Library Genesis)、Sci-Hub、Z-Library等主流影子图书馆的数据和资源。 永久保存整个人类的出版物,包括书籍、学术论文、杂志、漫画和各种图书馆元数据。平台上的所有代码和数据都完全开源,对所有人开放访问。 资源极其丰富:目前可检索近六千万本图书、九千五百万篇论文数据,包含来自LibGen、Sci-Hub、Z-Library等站点的内容,支持多语种检索。 学术延续性:虽然Sci-Hub暂停了新论文上传,但Anna's Archive的数据库“SciDB”继续直连学术论文资源。 开放存档与数据下载:所有数据均可批量镜像下载,支持种子文件,利于长久保存和分发。 多样化功能:覆盖资源搜索、元数据改进、志愿服务、开发者支持、版权声明、活动公告等板块,并不断发布相关博客和动态。 https://annas-arch…
火箭回收成功瞬间。 看马斯克的百米冲刺和真实反应。 优质「内容」 | 优质「资源」 | 你不知道的内幕消息🌳
👍2
Deepseek Harness 如果是 SDK 为主也能达到数据入口的效果吗? > 像 ZCode 这样的 Coding 产品,不只是变现工具,也可能成为数据入口:用户完成真实的软件工程任务,产生长周期执行轨迹,再反哺下一轮 Post-training,形成“产品使用 → 数据 → 模型升级 → 更多使用”的飞轮。 优质「内容」 | 优质「资源」 | 你不知道的内幕消息🌳
👍1
世界五大学习法: 1.费曼学习法:把学到的东西讲给别人听,能讲清楚,就算真学会了。 2.西蒙学习法:先定学习目标,再把它拆开,6 个月就能精通任意领域。 3.SQ3R 阅读法:浏览、提问、阅读、回忆、复习。 4.番茄学习法:把学习和休息排好,每段二十五分钟,定个闹钟。 5.康奈尔笔记法:把记和学、思考和运用结合起来,步骤是记录、简化、背诵、思考、复习五步。 优质「内容」 | 优质「资源」 | 你不知道的内幕消息🌳
❤1👍1
读完李笑来的《好的家庭教育》,手动整理些金句分享。 教育理念 ① 给孩子建立产权观念,不是我的,我不要。 ② 在家中,对书的需求必须无限制满足。 ③ 想要培养好孩子,第一,自己要做一个热爱生活的人。第二,尽可能把自己发展成榜样。第三,确保自己走在通往杰出的路上。 ④ 家庭教育的对象是家庭里的每一个人。 家庭关系 ① 家庭教育中,最重要的是夫妻关系。 ② 看一个人是否值得交往,就看对方的夫妻关系如何。一个人对自己的配偶都不好,怎么可能对一个外人好? ③ 家庭传承有三个判断标准。第一,子女数量。第二,子女团结程度。第三,子女离散程度,也就是指分散在不同的地理位置。 财富与经济 ① 从古至今赚钱方式只有三种:发现,生产和贸易,而放大收获的方式有两种:组织和积累。 ② 每个人都应该成为生产者。 ③ 经济上的自给自足是成人的判断标准。 ④ 从一份时间只能出售一次,升级到一份时间能出售很多次。 健康与生活习惯 ① 帮孩子养成每天运动15分钟…
👍2❤1
论文倒查,来了! 论文造假,从来不是什么新鲜事。 这些年,代写、数据造假、图片拼接、不当署名的新闻频频爆出,学术诚信的底线一再被触碰。 针对这个顽疾,不少高校陆续启动论文倒查,掀起一轮自查核查。 广州铁路职业技术学院、广东职业技术学院,划定从2017年起,倒查9年以来教职工发表的论文,排查买卖代写、图片重复、署名违规等问。 安徽建筑大学,倒查从2020年起,为期6年的科研成果,同步核查科研项目的数据真实性。 岳阳职业技术学院,回溯至2018年,覆盖论文、专著、专利等多项成果。从道理上讲,学术不端理应严肃查处,有错必究,发现一起,处置一起。 可问也随之而来:就算查出一批,处理一批,效果究竟能持续多久?能不能从根源上堵住造假的冲动? 优质「内容」 | 优质「资源」 | 你不知道的内幕消息🌳
👍1
经常找电子书的朋友,这个网站建议收藏。 推荐一个 Z-Library 发布页,整理了 Z-Library 相关访问入口和镜像地址,方便快速找到可用站点。Z-Library 喜欢看书、查资料、找电子版资源的,可以收藏备用。 🔗 https://zlibrary.me 优质「内容」 | 优质「资源」 | 你不知道的内幕消息🌳
👍1
#频道互推 你不知道的内幕消息🅥 Magazine|期刊杂志|考公|中文 | 网课分享 AI探索指南 互联网从业者充电站 书墨资源 出海🚢&自媒体运营秘籍 你不知道的冷知识 优质信息收藏夹 副业赚钱探索指南 两性知识 中年人生存报告 ──── 💡 互推: @jxht_bot
原神圣土化这个30天的任务如果不做,是不是所有人就都死了,神死了,七个国家几百个伙伴全死了,主角死了,派蒙也死了? 原神其实开放程度甚至不如武林群侠传(侠客风云传),好歹给你弄出来几十个结局,自己随便排列组合,可以当武林盟主,也可以干死所有人。 原神只有一个大结局,就是他妈包饺子。 优质「内容」 | 优质「资源」 | 你不知道的内幕消息🌳
👍1
这次厉害了。约 1000 个 Fable 5.2 智能体,只用 30 小时,就把费马大定理完整形式化成电脑能逐步验的证明。 同样配置下,Opus 5.5 跑了 18 小时只完成 26%。 同期还补完了一个从 2003 年一直没算完的黑洞问。 优质「内容」 | 优质「资源」 | 你不知道的内幕消息🌳
👍4
Showing the 12 most recent of 612 posts we hold for @chunse1024. 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 recorded as deleted after publishing
We recorded 19 posts on @chunse1024 as deleted — posts this register held that were missing from the channel’s public page on two separate reads, taken from different network addresses at least an hour apart.
A deletion is not wrongdoing. This register can see that a post it held is no longer on the channel’s public page, and when — not why. Expired ad placements, reposts, rotating links and corrections all look the same. This is a count of recorded detections, not an exact total: it misses deletions we could not see, because only a post we held and later re-read inside the page can be seen to go, and it may include a small number of wrong records. How this is measured.
- First seen missing
- 7 August 2026
- Most recent seen missing
- 11 November 2026
- Median time before seen missing
- 2 days
- Seen missing in the last 30 days
- 7
Forward network
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
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 25 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.
@https1024 · 31,5791,582 posts你不知道的内幕消息🅥
@inside1024 · 107,6981,508 postsAI探索指南
@aigc1024 · 37,620936 posts沙雕日常图鉴
@moyu2023 · 8,895567 posts副业赚钱探索指南
@text1024 · 20,334353 posts出海🚢&自媒体运营秘籍
@yunying23 · 21,796350 posts你不知道的冷知识
@knowledge1024 · 19,635332 posts优质「资源」收藏夹
@meiriyishu · 14,557303 posts中年人生存报告
@dogdairy · 14,261290 posts星辰观察站
@web2star · 8,413174 posts草台班子世界
@zheshijieya · 5,61547 posts极品风韵魅妇
@shaofu2026 · 2,96129 posts🍉 每日吃瓜【人间观察实录】
@doubannew · 4,01721 posts两性知识
@liangxing365 · 14,40321 posts书墨资源
@shumozy · 21,46319 postsChatGPT 精选
@AwesomeChatGPT · 15,21717 posts优秀設計分享
@jiaohusheji · 5,28917 postsfeelings yiheng
@feelingsyiheng · 13 posts零七八碎
@lingqibasui42 · 53 postsMagazine|期刊杂志|考公|中文 | 网课分享
@QiKan2026 · 49,8643 posts知识技能
@zhishijineng42 · 53 posts工具
@weichenjilu · 12 posts频道收藏推荐
@taobao1024 · 2,8011 post新宇宙
@yuzhou2088new · 21 post
Names
Channels on the register whose handles appear in this channel's posts.
@inside1024 · 107,698562 posts优质「资源」收藏夹
@meiriyishu · 14,557556 posts出海🚢&自媒体运营秘籍
@yunying23 · 21,79642 postsAI探索指南
@aigc1024 · 37,62041 posts中年人生存报告
@dogdairy · 14,26140 posts互联网从业者充电站
@https1024 · 31,57940 posts你不知道的冷知识
@knowledge1024 · 19,63540 posts两性知识
@liangxing365 · 14,40340 posts书墨资源
@shumozy · 21,46340 posts副业赚钱探索指南
@text1024 · 20,33440 posts沙雕日常图鉴
@moyu2023 · 8,89523 postsMagazine|期刊杂志|考公|中文 | 网课分享
@QiKan2026 · 49,8643 posts星辰观察站
@web2star · 8,4131 post草台班子世界
@zheshijieya · 5,6151 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.
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
@chunse1024 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 1 post, 5 November 2026 – 5 November 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 12 November 2026 — this entry's latest reading, not the date you are reading this.
“优质信息收藏夹” (@chunse1024), 28,732 subscribers as measured 12 November 2026. Telegram Register, tgregister.com/channel/chunse1024.
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.