Telegram RegisterThe public register of Telegram

Channel

LINUX DO Channel

@linux_do_channel

On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Handles named that no longer answer · Cite this entry

35,527subscribers

+291 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 31,623–100,000.

Register entry

Telegram ID-1002035446470
TypeChannel
Username@linux_do_channel
Descriptionhttps://linux.do 论坛的话题更新通知频道。
CreatedBetween 1 November 2023 and 31 May 2024— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live13 August 2026
Measurements held8
Confirmed unchanged1 time, most recently 13 August 2026
On Telegramt.me/linux_do_channel

Growth

35,23635,52735,381.57 August 2026 — 35,236 subscribers7 August 2026 — 35,236 subscribers8 August 2026 — 35,274 subscribers9 August 2026 — 35,302 subscribers10 August 2026 — 35,342 subscribers11 August 2026 — 35,432 subscribers12 August 2026 — 35,496 subscribers13 August 2026 — 35,527 subscribers7 August 202613 August 2026
8 measurements spanning 6 days, net +291. 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 35,192–35,571 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
13 Aug 2026, 06:5535,527+31
12 Aug 2026, 09:0235,496+64
11 Aug 2026, 12:0335,432+90
10 Aug 2026, 09:0635,342+40
9 Aug 2026, 08:4135,302+28
8 Aug 2026, 11:2935,274+38
7 Aug 2026, 15:3035,236no change
7 Aug 2026, 15:2335,236first reading

Engagement

340 posts held, back to 7 August 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 17 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
0.119%
avg views ÷ 35,527 subscribers
Avg views / post
42.2
340 posts measured
Reaction rate
0.885%
reactions ÷ views · ER floor
Posts in window
340
of 340 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 3 of 340 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 13 August 2026
Posts held340 (7 August 202613 August 2026)
Views total14,361
Reactions total2
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken13 Aug 2026, 09:30 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

Links
431,000

Lifetime counters from Telegram’s own channel header, read 13 August 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.

Reaction mix

2 reactions across 2 posts, in 1 kind.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
2100.0%

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 3 of the 340 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 2reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 340 most recent posts we hold, published 7 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

13 Aug 2026, 09:29 UTC1 viewsread 13 August 2026

Lucas (@lucaschungiii) 在 今天是我生日,下班给自己买个小蛋糕庆祝下吧 中发帖 女朋友也分手了,没人给我庆祝生日。自己凑合过下吧

13 Aug 2026, 09:29 UTC1 viewsread 13 August 2026

@fengchris 在 Gemini 3.7 Flash 要来了? 中发帖 [image] 反正pro版难产了,就刷flash版本号了

13 Aug 2026, 09:29 UTC1 viewsread 13 August 2026

Nicolas (@Nicolas_gong) 在 公司所有同事使用纯AI开发,目前想建立一些规范、制度统一下。你们有什么推荐嘛? 中发帖 公司从事web开发相关项目,严格区分前后端分工,后端还在使用PHP语言,自己有开源mcp测试工具,用来读mysql、redis、API等用于开发完成后测试回归接口工具。也建立一些技能、规则等相关文件,但是始终感觉还是差点意思,不知道差什么,不知道各位佬们开发是什么流程?

13 Aug 2026, 09:28 UTC1 viewsread 13 August 2026

哦豁 (@794466525) 在 佬们,30岁没结婚的有吗 中发帖 30岁没结婚正常吗,让我看看有多少人,大家都是多少岁结婚的。感觉现在结婚越来越晚了都

13 Aug 2026, 09:28 UTC3 viewsread 13 August 2026

ICeCream (@icexu330) 在 各位佬,想问问现在还有不坑的大流量卡用吗?跪求啊! 中发帖 如题所示各位佬,想问问现在还有不坑的大流量卡用吗?跪求啊!真的很后悔当时7月底没有办理 😭

13 Aug 2026, 09:28 UTC3 viewsread 13 August 2026

Seroton Karlbaey (@Karlbaey) 在 好玩,大数据杀熟 | Haku 中发帖 ← 返回首页 好玩,大数据杀熟 发布于 2026年5月24日 16:22 作者 Karlbaey #漫漫长路 #互联网 杀熟很常见,它有个更地道的称呼叫做“看人下菜碟”,但是互联网把这“人”,或者连人都不是,的范围扩得好宽好宽啊,甚至有时候奇形怪状的东西在网上爬动,我也不觉得奇怪了,反正林子大了什么鸟都有,何况是互联网这种黑暗森林。在这种环境里,有几百万个投机客蠢蠢欲动,那也再正常不过。反正投机改变的只是行为:从低买高卖变成了贩卖焦虑;至于本质,那还是没有变。 啊……我倒不是想说某些软件...

13 Aug 2026, 09:27 UTC5 viewsread 13 August 2026

aduang 在 local.ai 中发帖 一个关于本地模型能力比较的网站 欢迎使用我的注册链接:

13 Aug 2026, 09:26 UTC7 viewsread 13 August 2026

jerry_y (@hao_yan) 在 supergrok的3个月30美元值得买么 中发帖 [Screenshot_20260813_172136] grok 4.6能力如何,一个用量有多少

13 Aug 2026, 09:25 UTC7 viewsread 13 August 2026

昼夜 (@zhouyeshan) 在 警惕“保险退款”骗局,大家一定要提高防范意识 中发帖 事情经过是这样的:25 年我曾经在太平人寿购买过一份保险(这个保险也挺坑 😅),后来因为一些原因退保了,当时退回来的保费也没有多少。 今天突然接到一个自称是太平保险工作人员的电话,对方询问我的保险情况。我告诉他这份保险已经退保了,他说现在可以办理全额退款,但需要走一些流程。 我同意了,然后他跟我核实了一些个人信息,这些信息都是他说出来的,包括我之前的保险情况和相关资料,所以我当时没有产生太大怀疑。 核对完成后,他说需要验证银行卡,并给我之前购买保险时绑定的银行卡发送了一个签约验证码,说是保费后续会退到这个银行卡所以需要签约。 我当时没有多想,就直接把验证码告诉了他,然后他跟我说提交成功了,但是需要等待5到7天进行审核,后续还加了他的微信。 结果电话刚挂断没多久,我就收到银行卡扣款通知,被扣了500元,同时还收到了一条承保成功的短信。

13 Aug 2026, 09:25 UTC9 viewsread 13 August 2026

klyang (@kyle1106) 在 Grok 4.6 (xhigh)在Grokbuild中进行鹈鹕测试 中发帖 细节处理的真不错啊,车筐里还有一条鱼,很真实了哈哈 提示词就这一句: Generate an SVG of a pelican riding a bicycle [image] Token使用情况:加上系统提示词用了42.5k [Clipboard_Screenshot_1786610348] 应该是鹈鹕测试的来源?模型的空间能力和逻辑能力,鹈鹕和自行车的结构都很复杂,而鹈鹕的结构也不适合骑自行车,考验模型如何处理这些复杂的结构和关系。

13 Aug 2026, 09:25 UTC8 viewsread 13 August 2026

Kami958 在 看到自己的小工具被宣传真的是一件很有意思的事 中发帖 之前在github上开源了一个我用AI写的C盘变化对比的小工具(站内有帖),前些天在B站评论区也顺手发一下,今天有评论告诉我,他是被豆包推荐来的 🫪 [PixPin_2026-08-13_17-00-58] 然后才发现软件被一些软件站收录了,B站的up的测评文档也看到了,还有视频(我本来还打算自己发呢,不过最近很忙来着 🥲)。前段时间确实star涨的很快,我还以为是github或者L站有推流啥的 github上也没有什么 issue或反馈,我自己也忙没想到什么更新方向,就偶尔上去看看star,现在有一种突然刷到自己的感觉,好羞涩 😳

13 Aug 2026, 09:21 UTC10 viewsread 13 August 2026

Mumu (@MuStellar) 在 为什么鹈鹕骑自行车是大家测新模型的第一选择 中发帖 为什么新模型发了大家第一反应都是测一下鹈鹕骑自行车/糖果问题,这是L站benchmark吗,或者说有什么历史渊源,比如我记得很古早的生图模型测试,让它画“总线(bus)”,然后模型画了“巴士”,成为套壳国外模型的证据之一。这个鹈鹕骑自行车是否有类似理由,还是只是因为比较流行。

Showing the 12 most recent of 340 posts we hold for @linux_do_channel. 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 — 1,051,810 of 1,176,251entries 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.

Mentions

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.

Named by

Channels on the register whose posts name this channel's handle.

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.

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 13 August 2026 — this entry's latest reading, not the date you are reading this.

“LINUX DO Channel” (@linux_do_channel), 35,527 subscribers as measured 13 August 2026. Telegram Register, tgregister.com/channel/linux_do_channel.

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.