Channel
@MattersHub
On this record: Growth · Engagement · Reactions · Posts · Citations · Cite this entry
3,368subscribers
-14 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 3,162–10,000.
| Telegram ID | -1001290075159 |
|---|---|
| Type | Channel |
| Username | @MattersHub |
| 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 | 13 August 2026 |
| Measurements held | 4 |
| Confirmed unchanged | 1 time, most recently 13 August 2026 |
| On Telegram | t.me/MattersHub |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 13 Aug 2026, 02:34 | 3,368 | -7 |
| 10 Aug 2026, 00:02 | 3,375 | -7 |
| 6 Aug 2026, 16:34 | 3,382 | no change |
| 6 Aug 2026, 16:25 | 3,382 | first reading |
20 posts held, back to 27 September 2022 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 3 pagesof Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 20 posts for this entry, the most recent from 29 June 2023. An engagement rate over an empty window would be a number about nothing.
169 reactions across 17 posts, in 1 kind.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 👍 | 169 | 100.0% |
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 18 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 169reactions 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 27 September 2022 to 29 June 2023, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
回形针解散两年了，他们怎么样了？ 作者：草台班子 实际上，在这篇稿子的操作过程中，文中的受访者担心负面舆论影响现在的团队，一度希望删除自己的所有内容、本约好要发稿的平台因为被约谈而不得不放弃这篇稿件、而几家我们熟知的媒体也因为我们都知道但都不能说的风险而无法发表。这实在是一种太中国的处境了，这篇稿子和回形针的境遇从某种角度来说甚至是互文的。所以在征得所有受访者同意之后，我们决定自己把稿子发出来给大家免费看。如果你觉得还不错，可以转发或打赏支持。 透過 Solvers 閲讀 | 原文 #中国大陆 #回形针 #非虛構寫作
👍48
292 | 《人選之人》：全亞洲只有台灣拍得出的「選舉女子圖鑑」 作者：世界走走 seh seh 放眼整個亞洲，也只有台灣創作者會將「改變女性處境」放在與「改變國家未來」同等的高度。 透過 Solvers 閲讀 | 原文 #人選之人 #謝盈萱 #世界走走
👍15
上海解封的一年后，我离开了上海 作者：StephenYeong 一周年碎碎念，一点微小的个体记忆 透過 Solvers 閲讀 | 原文 #上海疫情 #上海 #上海封城
👍2
何必做一家人？ 作者：阿布拉赫 上周末去参加了一个小型的纪录片放映活动，《我们一家人》（All in My Family）。四十分钟的短片，记录了一个男同出柜、移民、代孕、探亲的历程。片子太短，和一个Vlog的体量差不多，大概是作者几次回国探亲的视频片段编辑整理而成。不过，已经足够真实到血淋淋的地步。 透過 Solvers 閲讀 | 原文 #同志 #All inMyFamily #我们一家人
逃离俄罗斯：“恐同法案”受害情侣呼吁更多人勇敢发声 作者：NGOCN 在俄罗斯，因为2022年11月新修订的“恐同法案”，中国留学生徐浩洋和他的同性伴侣Gela被指控有罪。如今，经历了被判囚禁和驱逐出境，这对被迫踏上流亡之途的情侣，依然坚持向世界发出自己的声音。 透過 Solvers 閲讀 | 原文 #俄罗斯 #国际不再恐同日 #LGBTQ
👍1
【年终总结】盘点2022年百大辱华分子 作者：世界之敌的敌人 转自微信公众号：世界之敌的敌人 透過 Solvers 閲讀 | 原文 #辱华
👍12
漸漸成長的 Matters Discord ：2022 年大事盤點 作者：Matty 2022年快要完結，2023年將至，Matters Discord 作為共學基地、閒聊場所，感謝大家今年的陪伴和共行。 透過 Solvers 閲讀 | 原文 #NFT #Discord #matters discord #Web3 #Matters
👍1
天國近了你當悔改：讀Joel Robbins《成為罪人》 作者：有關人類學 在暴風雪中聽聞黃應貴老師離去了，非常感慨。還是先貼出原本寫好的聖誕應景文章。出版於2004年、如今已成人類學基督教研究經典的Becoming Sinners，正是以一個「沈重」的聖誕故事開頭 。Robbins想要認真思考基督教對Urapmin人的意義，而人類學家又該怎麼書寫文化的劇變與斷裂？ 透過 Solvers 閲讀 | 原文 #Theology #Sin #Christianity #Papua #Anthropology
👍3
《人工智能的恶意使用：预测、预防和缓解》导读（全文） 作者：Worldme · 沃米 人工智能是一把双刃剑。AI技术既可以被用来造福社会，也可能被用于危害社会。因为AI能力强、扩展易，并且使用门槛低，加上AI本身的漏洞也非常危险，所以恶意使用造成的危害可能是巨大的。目前整个人类社会对AI潜在问题的警醒程度是不足的，所以如何对AI恶意使用问题进行研究和干预，成为越来越迫切的问题。 透過 Solvers 閲讀 | 原文 #元宇宙 #黑客攻击 #AI安全 #人工智能 #AI
👍3
當我們談論邊界時我們在談論什麼：讀Malini Sur《叢林護照》 作者：有關人類學 說到邊界，你會想到什麼？Malini Sur去年出版的Jungle Passport帶領讀者一窺印度與孟加拉邊境社會的困境與活力。對她而言，邊界與相對應的國家從來不先於人們而存在。在此生存許久的Garo人有自成一格的策略，屢屢挑戰了邊界帶來的壓迫與控制。 透過 Solvers 閲讀 | 原文 #Border Studies #South Asia #Landscape #Infrastructure #Anthropology
Si薰|我想要推薦 作者：si薰 我是si薰，要從創作了 819 篇作品，累積創作 635789 字中選出四篇推薦，着實不易，選出這四篇，都是自己心路歷程中，給自己影響深遠的文章，分享給大家 透過 Solvers 閲讀 | 原文 #徵文
👍2
白纸革命：一场“没有内容”的抗议 作者：扶霜 所以这场运动的诉求只能是一张白纸，因为没有任何一张纸能写满中国人的诉求，就不如什么都不写，正如我们什么都写了。站出来的人们不仅是为“部分居民没有自防自救能力”感到痛心，同时也注意到了一直以来被忽视的事实：当我们一再退让的时候，掉下悬崖的人，迟早轮到你我。 透過 Solvers 閲讀 | 原文 #中国 #白纸革命 #疫情之下
👍37
Showing the 12 most recent of 20 posts we hold for @MattersHub. 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 — 1,109,040 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.
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.
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 13 August 2026 — this entry's latest reading, not the date you are reading this.
“Matters | 閲讀精選” (@MattersHub), 3,368 subscribers as measured 13 August 2026. Telegram Register, tgregister.com/channel/MattersHub.
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.