Telegram RegisterThe public register of Telegram
Telegram profile photo for 笔记本:Lin's 文字世界 : 个人见闻/B站视频/网络见闻

Channel

笔记本:Lin's 文字世界 : 个人见闻/B站视频/网络见闻

@LinsBookA

On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Telegram's recommendations · Cite this entry

8,090subscribers

+80 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-1001420767960
TypeChannel
Username@LinsBookA
Description频道始于2019年6月,长期保持不太稳定的持续更新,内容主要以纯文字为主。伴有频道主的个人生活。 附属群聊:查看置顶 个人频道:https://t.me/LinYunChannel 小林的壁纸频道:https://t.me/linyunbook2 (暂停更新) 小林的头像频道:https://t.me/linyunbook4 (暂停更新)
CreatedBetween 1 April 2019 and 31 October 2021 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live12 November 2026
Measurements held24
Confirmed unchanged1 time, most recently 12 November 2026
On Telegramt.me/LinsBookA

Topic

Personal blog — 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 98% 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

8,0048,1078,055.56 August 2026 — 8,010 subscribers6 August 2026 — 8,010 subscribers9 August 2026 — 8,015 subscribers12 August 2026 — 8,004 subscribers16 August 2026 — 8,014 subscribers19 August 2026 — 8,012 subscribers23 August 2026 — 8,020 subscribers26 August 2026 — 8,014 subscribers29 August 2026 — 8,015 subscribers1 September 2026 — 8,019 subscribers10 September 2026 — 8,024 subscribers19 September 2026 — 8,031 subscribers29 September 2026 — 8,088 subscribers6 October 2026 — 8,068 subscribers12 October 2026 — 8,052 subscribers19 October 2026 — 8,059 subscribers22 October 2026 — 8,064 subscribers25 October 2026 — 8,061 subscribers27 October 2026 — 8,064 subscribers31 October 2026 — 8,071 subscribers2 November 2026 — 8,078 subscribers5 November 2026 — 8,080 subscribers8 November 2026 — 8,107 subscribers12 November 2026 — 8,090 subscribers8,0906 August 202612 November 2026
24 measurements spanning 98 days, net +80. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 7,989–8,122 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 24
Measured (UTC)SubscribersChange
12 Nov 2026, 17:518,090-17
8 Nov 2026, 10:408,107+27
5 Nov 2026, 15:558,080+2
2 Nov 2026, 19:078,078+7
31 Oct 2026, 03:408,071+7
27 Oct 2026, 22:568,064+3
25 Oct 2026, 07:088,061-3
22 Oct 2026, 17:498,064+5
19 Oct 2026, 16:098,059+7
12 Oct 2026, 22:108,052-16
6 Oct 2026, 09:228,068-20
29 Sept 2026, 09:428,088+57
19 Sept 2026, 08:358,031+7
10 Sept 2026, 22:198,024+5
1 Sept 2026, 13:088,019+4
29 Aug 2026, 17:238,015+1
26 Aug 2026, 14:538,014-6
23 Aug 2026, 06:088,020+8
19 Aug 2026, 14:438,012-2
16 Aug 2026, 15:148,014first reading

Engagement

81 posts held, back to 22 July 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 39 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
9.50%
avg views ÷ 8,090 subscribers
Avg views / post
769
31 posts measured
Reaction rate
0.829%
reactions ÷ views · ER floor
Posts in window
31
of 81 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 24 of 31 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 12 November 2026
Posts held81 (22 July 2026 – 12 November 2026)
Views total23,836
Reactions total159
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken13 Nov 2026, 01:44 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

Photos
≈1,260
Videos
≈16
Links
≈1,190

Lifetime counters from Telegram’s own channel header, read 13 November 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.

Video runtime
47m 29s
Average length
23m 45s

Measured directly from 2 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

307 reactions across 48 posts, in 22 distinct kinds. The most used accounts for 20.2% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤6220.2%
👍4113.4%
😁3210.4%
😢3210.4%
🤣309.77%
🤯216.84%
👏206.51%
😇144.56%
🤔82.61%
😱72.28%
🐳61.95%
😭51.63%
👌41.30%
😨41.30%
🥰41.30%
🥱41.30%
👎30.977%
🤡30.977%
🤷‍♂30.977%
🤮20.651%
2 further kinds20.651%

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 51 of the 81 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 307 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 81 most recent posts we hold, published 22 July 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: 4 of 31 posts held from the last 30 days (12.9%) 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).

12 Nov 2026, 17:58 UTC222 viewsread 13 November 2026
Photo

【老蒋巨靠谱】字节拿大结果,你拿大红果 最近“字节时间”引发关注。有媒体统计,字节系产品占到中国人手机使用总时长的41.8%,比一年前的34.2%增加7%,新增几乎都来自上线两年的红果短剧。红果目前月活达4.3亿,在所有应用里时长排第四,用户日均刷166分钟。老蒋先表态自己佩服字节的管理与产品能力,也反对粗暴或政治化的批判,但他想聊聊这件事背后的创作变化与商业伦理问题。 在创作端,AIGC带来了普惠,也藏着悖论。高概念作品指的是核心魅力来自奇特设定的影视内容,比如最近很火的一部AI短剧,讲特种兵带防弹衣和枪械穿越到宋朝。过去这类题材制作昂贵,只有大机构拍得起,现在AI大幅降低了落地门槛。但老蒋认为普通人很难借此持续赚钱。个人创作者花一两个月才做20分钟短片,供不上用户日均近3小时的消耗;平台需要的是按数据反馈快速迭代、工业化复制爆款的团队,还得买得起市场验证过的网文版权。最后能稳定赚钱的往往是10到20人的小团队,规模比真人…

Signed codexLinYun

12 Nov 2026, 16:36 UTC490 views20 reactionsread 13 November 2026

AI确实牛逼,黄仁勋都失业了

🤣18😇2

11 Nov 2026, 02:51 UTC565 views6 reactionsread 13 November 2026
Photo

【宝玉】AI 编程面试也不见得更容易 宝玉分享了一位 Reddit 用户的彭博社面试经历。这位求职者认为,允许使用 AI 的编程面试比刷 LeetCode 更难应对,原因是代码库庞大、时间有限,面试官对 AI 使用程度的期望也不明确。 这位求职者参加的是第二轮代码库面试,题目涉及他不熟悉的 Python Django 框架。前半小时用于行为面试,剩下约半小时写代码。他花了不少时间理解代码库和定位问题,又要阅读 AI 生成的内容,同时与面试官沟通。 他使用 AI 的规划和提问模式逐个推进功能,通过了部分测试,最后仍被拒绝。他还说,一位朋友让 AI 用一条提示词完成整道题,也遭到了拒绝。这段经历让他觉得,AI 面试很难找到稳定通用的应对方法。 #x #AI编程 #技术面试 source

👍4👏1🔥1

Signed codexLinYun

8 Nov 2026, 17:51 UTC759 viewsread 13 November 2026
Photo

【colsto】这段背景音会泄露你的精确位置 一段画面几乎静止、拍摄于美国本土的普通监控录像,仅凭人耳无法听清的背景噪音,就能精确定位到具体的摄像头位置。博主colsto展示了利用螺旋桨飞机音频多普勒效应进行地理定位的全过程。 视频音频在频谱图放大后,能看到螺旋桨飞机留下的多普勒频移曲线。物体朝向和远离观测者时声音频率会改变,下降幅度反映飞行速度,下降快慢取决于飞机与地面的最近点距离。结合公开的美国全境航班飞行轨迹数据以及数字高程模型,首先找出九百二十秒内相继飞过同一区域的两架螺旋桨飞机。考虑到繁忙机场周围频繁经过航班,而这两次飞机声之间存在近十五分钟的彻底静默,静默时间成为了强有力的排除条件,将全美数十万个网格点缩减到一万五千个。 为了进一步锁定,作者对候选航迹建立三维声学模型,基于真实飞行姿态与声音传播延迟,计算每个地面观测点理应听到的理论多普勒曲线,并与实际频谱打分匹配。在两趟航班双重锁定的高精度计算下,最高分候选点…

Signed codexLinYun

7 Nov 2026, 07:21 UTC930 views7 reactionsread 13 November 2026
Photo

deepseek 官方服务出现中断

🐳6👍1

6 Nov 2026, 16:27 UTC868 views5 reactionsread 13 November 2026
Photo

中文开源字体集:OSFCC 做中文排版时,真正让人费时间的往往不是找到一款好看的字体,而是确认它能不能放心使用。OSFCC(Open Source Fonts Collection for Chinese)收集了一批带有明确开源授权协议、可用于中文字体排印的字体项目,试图把分散在各处的资料整理到一起。 这个集合的标准是:免费获取不等于开源,闭源但免费的字体不在收录范围内。页面特别强调授权协议,因为中文字体的购买、使用和分发边界经常说不清,使用者可能面对不必要的法务纠纷。收录项目包括 SIL Open Font License、GPL、Apache 2.0、BSD、CC 等协议,具体使用时仍需查看对应项目的授权条款。 OSFCC 的表格不只列字体名称,还记录开发者、字体样式、字重数量、授权协议,以及简体、繁体、日文、韩文的支持情况。思源黑体、思源宋体和思源等宽支持七种字重,并覆盖这四种语言;更纱黑体、昭明黑体、文泉驿系列、花…

👍5

Signed codexLinYun

6 Nov 2026, 16:01 UTC668 views3 reactionsread 13 November 2026
Photo

居然被收录了,感谢 https://github.com/TGrpg/awesome-telegram

❤3

6 Nov 2026, 14:06 UTC664 views14 reactionsread 13 November 2026

直到现在我都觉得这一切很玄幻。 今晚 10 点半接到了一个陌生号码的电话,我还以为是我点的超市快送就接了,结果发现是我中午点的外卖店员,因为我今天中午给了一条中评,说他们家的鱼变小了。 我一开始非常生气。他在电话那头支支吾吾地问我有什么诉求之类的,我说,我没有诉求,我只是一五一十地陈述我最近几次点的鱼就是随着你们换包装之后比之前个头要小了,我想知道你们是 SKU 换了,还是说这只是偶然的事情? 对面大约是个年纪不太大的男生,声音也有些疲惫,他说他们没有换,都是公司统一配送的鱼。其实我能听出来有可能公司真的调整了策略,只是他没有任何决定权。他说看您也是老客户了那您下次可以备注,免费送您一条可不可以。 我说我不需要,以及我问他的诉求是什么,是让我删评吗。他说也不是,就是店长要求他们一定要了解顾客的诉求,跟顾客道歉以及之后改进。 我没忍住:那你半夜 10 点半给我打电话,你觉得你是在向顾客了解诉求,还是在骚扰顾客? 他变得…

😢11👍2🤔1

5 Nov 2026, 16:32 UTC647 views7 reactionsread 13 November 2026

【百度】ERNIE 5.5 Flash Base 发布:280B 总参数,单 token 激活 14B 11 月 5 日,百度在官方 X 账号宣布 ERNIE 5.5 Flash Base 发布。这是一个稀疏 MoE 语言模型,训练数据覆盖多个领域与语言,百度称它在同规模基座模型的多个基准上达到 SOTA。 架构和训练系统是配套设计的,目标是在训练与推理两端都保持效率,改动集中在注意力机制、专家路由和训练目标三处。规模方面,总参数 280B,每个 token 激活 14B;预训练消耗 33.5T token;微调与推理支持最长 100 万 token 上下文;权重提供 FP8 与 BF16 两种精度。 百度强调放出的是纯预训练权重,没有经过中期训练和后期训练。官方给出的用法是从同一个 checkpoint 出发对比各种方法,看每种方法各自能带来多少增益,再按自己的任务去调整模型。 #百度 #ERNIE #大模型 #x […

🥱3❤1👍1👎1😁1

5 Nov 2026, 05:30 UTC620 views7 reactionsread 13 November 2026
Photo

【罐头辰Danny】游戏语言,好像正在替年轻人说真心话 想约朋友出门,直接说“最近状态差、需要人陪”会让人愣住,换成“晚上三排吗”就说得出口;谢谢同事说“非常感激您以后继续指教”像敬酒词,换成“哥以后还得靠你带飞”就自然了。作者罐头辰Danny认为,这类游戏用语正在替年轻人说真心话,所以标题起得夸张。 中文一直靠吸收词汇长大:佛教带来世界、烦恼、刹那,丝绸之路带来琵琶、骆驼,近现代有了沙发、咖啡、逻辑,社会科学和哲学经日本转译回来。行业黑话同样会进来,厂矿的掉链子、开足马力,曲艺的现挂、包袱。游戏是八零后到零零后的共同经验,自然也在往中文里添词。 作者拿标题去问一位三十五岁、在211高校教中文的老同学,本以为会得到夸奖,对方却把这些词批了一通:任何情绪都叫破防,人会慢慢失去描述复杂感受的能力;社会问题说成版本不行或系统有 bug,该有的追问被一起解构;不懂游戏的老人被挡在讨论之外。中国之声二〇二六年九月的报道援引调查,53…

❤4👍2😢1

Signed codexLinYun

4 Nov 2026, 04:45 UTC669 views10 reactionsread 13 November 2026
Photo

【啊达杂谈】作为casino荷官,我见证了一个人从娱乐变成了赌徒 作者是洛杉矶赌场的一名荷官,他见过一个中国留学生怎么从娱乐变成赌徒。这人刚来时被朋友带来玩德州扑克,也在家和同学玩,输了钱但不至于借钱撒谎。后来他越玩越多、越输越多:洛杉矶赌场一到三百美元的桌子,一手抽七美元水钱,赢了还要给荷官一块小费,长期算下来赢不了,私局和赌场里作弊的也多。他不认输,别人又愿意教,输了大量钱,接着染上百家乐,学校不去了,家里还以为他在好好读书。 作者在饭桌上见过他给妈妈打电话:说同学都买车,他也想买,想谈女朋友带个儿媳回去,骗到钱就去赌。半年后再见,他二十二岁看着像三十二,满脸胡须,对吃饭、谈恋爱、打篮球都没感觉,只有摸牌时脑子才活过来。 妈妈替他还了太多次同学的债,已经不给钱,放弃了他。一次他堵在作者车里借一万,先说家里住着放高利贷的人,当天还不上会被打死,再降到五千、一千,全是谎话;最后让作者配合骗他妈,说欠了房租、不还就打他。作者…

😢10

Signed codexLinYun

Showing the 12 most recent of 81 posts we hold for @LinsBookA. 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.

Forward network

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 5 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.

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.

Appears in Telegram’s recommendations for other channels

The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.

桔梗书屋
@JGBOOK · 21,912
Telegram ranks this channel #15 of 34 here — alongside 33 others — read 24 September 2026
树洞🌳群友问❓有点意思🗳
@qunyouwen · 89,030
Telegram ranks this channel #20 of 67 here — alongside 66 others — read 17 August 2026
秘密小频道(树洞)
@chxpd · 157,324
Telegram ranks this channel #23 of 51 here — alongside 50 others — read 17 August 2026
飛蛾書庫
@MothLib · 35,344
Telegram ranks this channel #35 of 50 here — alongside 49 others — read 3 September 2026
平壤卫视
@pingrangTV · 29,366
Telegram ranks this channel #44 of 45 here — alongside 44 others — read 8 September 2026
上班划水之无聊图
@goworkbitch · 25,325
Telegram ranks this channel #46 of 52 here — alongside 51 others — read 15 September 2026
黑洞资源笔记
@piracy6 · 78,065
Telegram ranks this channel #56 of 61 here — alongside 60 others — read 19 August 2026

This channel appears in 7 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.

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.

“笔记本:Lin's 文字世界 : 个人见闻/B站视频/网络见闻” (@LinsBookA), 8,090 subscribers as measured 12 November 2026. Telegram Register, tgregister.com/channel/LinsBookA.

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.