Channel
@haotalk
On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
2,763subscribers
+0 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 1,000–3,162.
| Telegram ID | -1001128365706 |
|---|---|
| Type | Channel |
| Username | @haotalk |
| Description | 郝海龍的個人 Channel，你可以理解成另一種形式的博客或者微博客，歡迎喜歡我的人訂閱關注。也歡迎大家： - 給我寫信 hi@haohailong.net - 歡迎關注 twitter.com/haohailong - 更多信息 bio.link/haohailong |
| Created | 17 July 2017 — measured — cross-checked against a third-party dataset (TGDataset) |
| First recorded | 6 August 2026 |
| Last confirmed live | 12 August 2026 |
| Measurements held | 2 |
| On Telegram | t.me/haotalk |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 6 Aug 2026, 05:17 | 2,763 | no change |
| 6 Aug 2026, 02:34 | 2,763 | first reading |
20 posts held, back to 15 March 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 2 pagesof Telegram’s post history, 20 posts per page.
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 5 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 31 July 2026 |
|---|---|
| Posts held | 20 (15 March 2026 – 31 July 2026) |
| Views total | 2,535 |
| Reactions total | 4 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 7 Aug 2026, 16:11 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.
Lifetime counters from Telegram’s own channel header, read 7 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.
61 reactions across 11 posts, in 7 distinct kinds. The most used accounts for 57.4% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 35 | 57.4% | |
| 🤔 | 10 | 16.4% | |
| 👍 | 6 | 9.84% | |
| 🥰 | 5 | 8.20% | |
| 👏 | 2 | 3.28% | |
| 🤣 | 2 | 3.28% | |
| 🌭 | 1 | 1.64% |
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 12 of the 20 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 61reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 20 most recent posts we hold, published 15 March 2026 to 31 July 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.
图片来自东野圭吾1987年作品《学生街的日子》，这么有预见性吗？ 那时我还没有出生，我出生后十几年才第一次摸到电脑。然而就在那个时代日本就开始让程序员35岁退休了？中国做这决定的老板是不是刚好看到了东野圭吾的小说？ 但不得不说看东野早期作品是需要一点耐心的，哪怕是《放学后》也没有那么容易读完。中国的宣传爱说江户川乱步奖是日本推理小说最高荣誉，导致很多人难免会有「最高水平就这」的感觉，但其实乱步奖很早就变成了推理新人出道奖，真正的最高水平得看直木奖。 不过直木奖有直木奖的问题，一个是不光给推理小说，另一个就是颁发频率太高了，一个最高荣誉一年颁发两次里面难免有凑数的。 #东野圭吾
🤣1
主播说的他在初中时的经历，我也差不多经历过类似的。 https://youtu.be/V2n3aUkNoHU
👍2🌭1
#博客更新 郝海龙读过的东野圭吾作品列表：纪念东野圭吾先生 https://haohailong.net/2026/hao-hai-long-du-guo-de-dong-ye-gui-wu-zuo-pin-li-f8295bc9
刚刚数了一下，大约读过他65部作品。
日本小说家东野圭吾本月23日因大肠癌去世，享年68岁。 https://news.web.nhk/newsweb/na/na-k10015187291000
有几件发生在我身上的事情很奇妙： 1. 小时候有一次穿过格子衬衣，后来很长时间就再也没有穿过（买不到），于是有段时间比较喜欢穿格子衬衣，可不知为什么这就变成了程序员标配，被当作没有审美或审美偷懒的表现。 2. 中学时有一次我感觉异常寒冷，预计很快就要生病，自己喝了两碗热水，睡了一觉，然后奇迹般好了。从那时起，我就经常劝人多喝热水，但不多久之后这就变成了「直男癌」的表现。 3. 我写非虚构类文章喜欢用「不是……而是……」，然后你们知道最近这变成了AI的特征。（难道不是因为在非虚构文章的场合，这种表达很好（虽然可能也是Cliché，但中文的成语都是Cliché啊），才被AI学走吗？）
🤔10❤3
郝海龙《重复：或许是最重要的说服方式｜自我教育04》 本文于2022年5月首发于会员通讯《林中来信》，同时也是「自我教育」系列第 4 篇文章。最近看到李笑来老师新书《The Half Second》当中提到了很多与本文相关的观点，于是决定免费释出，供大家参考阅读。 https://haohailong.net/2026/zhong-fu-huo-xu-shi-zui-zhong-yao-de-shuo-fu-fan-d719b147 #博客更新
推荐一个 NeoDB 的客户端「别录.」。可以通过浏览器添加到手机桌面，体验堪比原生应用。 （链接为作者的 Mastodon，大家不要被账号名字误导…… https://mastodon.social/@Shinnki1994/116546219487056923
❤4
「第欧根尼俱乐部」关停通知（2026） https://haohailong.net/2026/di-ou-gen-ni-ju-le-bu-guan-ting-tong-zhi-e07f0712
更正启事与叶李华老师新节目推荐 - 环尾堂 https://haohailong.net/2026/geng-zheng-qi-shi-yu-xie-li-hua-lao-shi-xin-jie-94d35f89
日本旅行之在富士急坐过山车 https://haohailong.net/2026/ri-ben-lu-xing-zhi-zai-fu-shi-ji-zuo-guo-shan-ch-c40ba94c
👍4
东京旅行之便利店 https://haohailong.net/2026/dong-jing-lu-xing-zhi-bian-li-dian-2af2d0bf
👏2🤣1
Showing the 12 most recent of 20 posts we hold for @haotalk. 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 — 218,923 of 1,160,990entries 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.
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.
Named by 4 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.
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.
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 6 August 2026 — this entry's latest reading, not the date you are reading this.
“海龍說” (@haotalk), 2,763 subscribers as measured 6 August 2026. Telegram Register, tgregister.com/channel/haotalk.
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.