Channel
@xhqcankao
On this record: Topic · Observations · Also posting the same content · Growth · Engagement · What this channel posts · Reactions · Stars · Posts · Citations · Telegram's recommendations · Cite this entry
163,238subscribers
+7,763 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 100,000–316,228.
| Telegram ID | -1001472283197 |
|---|---|
| Type | Channel |
| Username | @xhqcankao |
| Description | 风闻奏事，遍查访知。提供互联网科技新闻快讯。发布VPS、网盘等有价值虚拟资产的新闻和交易信息。⚡️ 本频道引用的所有文章皆旨在拓宽信息视野，不代表本频道观点。本频道谢绝任何政治频道转发消息，请勿让我们的评论区变成一个火药桶。请以包容友好的方式交流。 🏆 合作咨询：https://t.me/HelloGeorge_Bot |
| Created | 5 December 2020 — measured — cross-checked against a third-party dataset (ext.tg_channel) |
| First recorded | 6 August 2026 |
| Last confirmed live | 18 September 2026 |
| Measurements held | 35 |
| Confirmed unchanged | 1 time, most recently 18 September 2026 |
| On Telegram | t.me/xhqcankao |
Technology — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 9 August 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 why it has no browse page of its own yet.
These are measurements, not verdicts. Each one below states something we counted, alongside the evidence it was counted from, so you can check it rather than take it. None of them is graded: every observation this register holds is recorded at severity 0, because the precision of the detectors behind them has not been measured yet, and a rating we cannot support is worse than none. Read each as a fact about the data, not as a judgement about the channel. How we measure.
Posts published here appear word for word on 3 other registered channels. They sit inside a group of 5 channels that share the same post bodies with each other. The matching is on the text itself, not on Telegram’s forward marker, so it finds a copy whether or not it was labelled as one.
| Posted first | Then | Overlap | Gap |
|---|---|---|---|
| @xhqcankao/31287 · this entry7 Aug 2026, 01:31 UTC | @xinxianshi/479147 Aug 2026, 02:51 UTC | 1.00 | 80 minutes |
| @xhqcankao/31288 · this entry7 Aug 2026, 02:01 UTC | @xinxianshi/479157 Aug 2026, 02:51 UTC | 1.00 | 50 minutes |
| @xhqcankao/31289 · this entry7 Aug 2026, 02:31 UTC | @xinxianshi/479167 Aug 2026, 02:51 UTC | 1.00 | 20 minutes |
| @xhqcankao/31292 · this entry7 Aug 2026, 04:03 UTC | @xinxianshi/479197 Aug 2026, 04:18 UTC | 1.00 | 14 minutes |
| @xhqcankao/31293 · this entry7 Aug 2026, 04:30 UTC | @xinxianshi/479207 Aug 2026, 05:45 UTC | 1.00 | 74 minutes |
| @xhqcankao/31294 · this entry7 Aug 2026, 05:03 UTC | @xinxianshi/479217 Aug 2026, 05:45 UTC | 1.00 | 42 minutes |
| Channel | Matching posts | Text overlap | Typical gap | Published first |
|---|---|---|---|---|
| @xinxianshi | 15 (8/8 hand-verifiable sample passed) | 1.00 | 44 minutes | this entry (15–0) |
| @NEWSPJAPK | 15 (7/8 hand-verifiable sample passed) | 1.00 | 10 minutes | this entry (15–0) |
| @kejidiyixian | 6 (6/6 hand-verifiable sample passed) | 1.00 | 12 minutes | this entry (6–0) |
Text overlap is the Jaccard coefficient over the set of distinct three-word phrases in the two bodies: 1.00 is identical wording, and the threshold for counting a pair at all is 0.70. Candidates are generated by simhash LSH (4 x 16-bit bands, exact Hamming <= 3) verified against the bodies with Jaccard over the SET of distinct 3-word shingles. Published first counts which side of each matching pair carries the earlier timestamp — in this corpus, which is the limitation directly below.
What this cannot establish
MEASURED, DOMINANT ERROR SOURCE: a post ingested before 2026-08-06 may have carried a forward header that was not recorded. A 45-pair hand-check against live t.me pages found 14 (31%) where the live page shows a forward header naming the other channel and the database has none, plus 4 more (9%) naming a third party. The text match itself was wrong 0 times out of 45. Read attribution_capture.items_in_trusted_window before treating the unattributed count as a claim.
Telegram lets a channel forward a post with a header naming the source, and we only began reliably recording that header on 2026-08-06. None of the 0 matches recorded here fall after that date, so for this entry we cannot say whether any of them carried a credit. The duplication is measured; the absence of attribution is not.
“Published first” means first in this corpus. We hold 43 comparable posts for this entry, running 5 August 2026 to 7 August 2026. A channel we have read one page deep will look younger than a neighbour we have read in full, and the order would flip with no change in the underlying facts.
The detector’s own notes on this observation, as it recorded them. Names in this_style are fields of the underlying evidence record, which the plain-English paragraphs above read out for this entry.
Across the whole group of 5, the earliest publisher we hold is @xhqcankao — which is this entry. That is a statement about our reading window, not a claim of authorship.
Recorded under the key clone_source, last confirmed 8 August 2026. An observation that a later pass no longer finds is cleared, and a cleared observation is removed from this page rather than being shown struck through — we do not keep publishing a claim we have withdrawn. Dispute an observation.
This channel’s posts match, word for word or near enough, posts on 4 other registered channels, found by comparing text fingerprints across every channel on the register. That matching has been checked by hand against the live Telegram pages and found reliable — 0 wrong of 45 pairs re-read.
Which channel, if either, published first is deliberately not shown. The same hand-check found that reading wrong 18 of 45 times — 60%, no better than a coin flip — because it depends on how deep our own crawl happened to reach into each channel’s history, not on when the content was actually first posted. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Word-for-word matching has several ordinary explanations besides copying — a channel mirroring itself, an unattributed repost, or two channels independently repeating the same wire story — and this measurement cannot tell those apart. How this is measured.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 18 Sept 2026, 03:17 | 163,238 | +160 |
| 15 Sept 2026, 18:58 | 163,078 | +142 |
| 13 Sept 2026, 23:38 | 162,936 | +288 |
| 12 Sept 2026, 08:40 | 162,648 | +1,369 |
| 10 Sept 2026, 04:42 | 161,279 | +965 |
| 6 Sept 2026, 19:38 | 160,314 | +155 |
| 4 Sept 2026, 04:21 | 160,159 | +101 |
| 2 Sept 2026, 21:17 | 160,058 | +33 |
| 1 Sept 2026, 21:07 | 160,025 | +41 |
| 31 Aug 2026, 19:07 | 159,984 | +96 |
| 30 Aug 2026, 16:02 | 159,888 | +77 |
| 29 Aug 2026, 12:52 | 159,811 | +59 |
| 28 Aug 2026, 16:22 | 159,752 | +66 |
| 27 Aug 2026, 15:06 | 159,686 | +71 |
| 26 Aug 2026, 16:23 | 159,615 | +75 |
| 25 Aug 2026, 19:35 | 159,540 | +73 |
| 24 Aug 2026, 22:06 | 159,467 | +103 |
| 23 Aug 2026, 05:14 | 159,364 | +128 |
| 21 Aug 2026, 13:57 | 159,236 | +89 |
| 20 Aug 2026, 11:09 | 159,147 | first reading |
849 posts held, back to 5 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 98 pages of 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.
| Window | Rolling 30 days · latest post in window 22 September 2026 |
|---|---|
| Posts held | 849 (5 August 2026 – 22 September 2026) |
| Views total | 3,998,960 |
| Reactions total | 54,672 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 22 Sept 2026, 20:05 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 22 September 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.
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.
83,258 reactions across 829 posts, in 69 distinct kinds. The most used accounts for 18.4% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 👍 | 15,279 | 18.4% | |
| 🤡 | 14,759 | 17.7% | |
| 😁 | 13,939 | 16.7% | |
| 💩 | 8,152 | 9.79% | |
| 🤣 | 4,676 | 5.62% | |
| 👎 | 3,026 | 3.63% | |
| ❤ | 2,836 | 3.41% | |
| 🖕 | 2,375 | 2.85% | |
| 👏 | 2,249 | 2.70% | |
| 🤮 | 1,846 | 2.22% | |
| 🐳 | 1,335 | 1.60% | |
| 🤯 | 1,257 | 1.51% | |
| 😱 | 1,167 | 1.40% | |
| 🔥 | 910 | 1.09% | |
| 🤔 | 905 | 1.09% | |
| 🍾 | 895 | 1.07% | |
| 🎉 | 678 | 0.814% | |
| 🫡 | 592 | 0.711% | |
| 🥰 | 515 | 0.619% | |
| 😢 | 451 | 0.542% | |
| 49 further kinds | 5,416 | 6.51% |
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 849 of the 849 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 84,327 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 849 most recent posts we hold, published 5 August 2026 to 22 September 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.
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @xhqcankao. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.
Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.
This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.
Counted over the 849 most recent posts we hold for this entry, published 5 August 2026 to 22 September 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.
白宫宣布推出流媒体频道“特朗普电视” 美国白宫21日推出了自己的在线流媒体频道“特朗普电视（Trump TV）”。在当天早些时候，美国各大电视网的白宫记者团罕见暂停了对特朗普的联合报道。“特朗普电视” 是一个在YouTube上24小时播放的频道，于当地时间21日晚间开播，首段视频是特朗普于7月3日在拉什莫尔山发表讲话的直播画面。 特朗普18日禁止CNN、Politico和MS NOW的白宫记者进入白宫，理由是他们 “不断‘报道’假新闻！” 作为回应，美国四家主要电视网21日宣布暂停白宫电视记者联席团对特朗普的相关报道工作。 —— 新华社、澎湃新闻
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微软启动新一轮裁员：涉及约500名员工 集中在Xbox游戏部门 微软于周二启动新一轮裁员，涉及约 500名员工，主要集中在 Xbox 游戏部门，云与AI等其他业务部门也有少量岗位受到影响。 本次裁员发生在7月裁员之后。微软当时宣布裁减全球员工总数的2.1%，约4800人。经过多年扩张与大额收购，微软正着手精简游戏业务，本轮裁员是该举措的最新一步。 Xbox正在推进一项计划：在本财年末削减约20%员工，同时重组旗下工作室，并梳理保留业务清单。Xbox此次“重组”的最新动作包括裁撤268个游戏相关岗位、重组Xbox工作室群，以及披露资产剥离计划的最新进展。 —— 新浪财经
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苹果正在开发iPhone被盗检测锁定功能 最新 iOS 27.2 beta 中的新引用显示，苹果公司仍在继续开发一项新功能，该功能将在iPhone被小偷从手中抢走时锁定手机。该功能据报道将使用陀螺仪、加速度计和其他传感器来判断iPhone何时被抢夺。还将依靠配对的苹果手表来检测iPhone何时突然远离主人的手腕。根据新代码，该功能在内部被称为“AutoLock”，可以使用几种不同的方法来判断iPhone是否已从其主人手中被抢走： 与手机被抢走相吻合的剧烈加速度；已配对的Apple Watch在一定时间内持续处于无法连接状态；与已配对的Apple Watch失去连接；网络连接长时间丢失；设备在超过一定时间间隔后仍保持未锁定状态。 —— Macrumors
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特朗普与习近平的峰会不太可能邀请中国企业高管 据知情人士透露，中国国家主席习近平本周晚些时候前往华盛顿会晤美国总统特朗普时，不太可能率领企业高管代表团随行；这降低了外界对此次峰会能达成重大商业协议的预期。一些获悉习近平访美行程的业内人士此前曾预计，中方会组织一个由高管组成的代表团随同习近平出访。这些人原本预计，中国高管将与来自美国科技和人工智能领域的顶级企业首席执行官一道，出席特朗普于周四举行的国宴。有关习近平访美的筹备工作仍在进行中，具体安排仍有可能发生变化。中国企业代表团很可能缺席，这一情况凸显出外界对这两大全球经济体领导人会晤能取得重大商业成果的预期较低。政治紧张局势限制了中国大型企业在美国进行生产投资的能力，而此类投资通常是外国企业高管造访华盛顿时的重要议题。 —— 华尔街日报
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蒸馏美国AI模型反致国家数据外泄，深度求索与月之暗面遭网信办调查 路透社22日引述新闻网站The Information快讯报道，中国网信办已对知名人工智能科技公司深度求索及月之暗面进行调查，两家公司可能涉及在「蒸馏」美国AI模型的过程，让中国国家级数据外流。 美国AI巨头之一的Anthropic本月稍早惊爆，深度求索及月之暗面曾使用其语言模型Claude处理自家用户的请求，再将答案冒充成自己的成果。月之暗面旗下模型Kimi用户曾上传中国监视摄影机的视频资料，其中包括解放军设施外的监视画面，可能导致国家机密流入美国。此外，阿里巴巴、小米等高层也已被约谈。 —— TheInformation ， Yahoo新闻
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三星将在部分智能手机电池中添加安全芯片 据The Elec报道，三星导致将在其部分手机的电池中添加安全芯片。该公司显然将把这个芯片添加到即将推出的中端手机内的电池中，包括Galaxy A系列。尚不清楚这些安全芯片将如何使用，但该媒体推测，三星可能将这些芯片作为安全措施的一部分添加。经过验证的电池应该能让消费者安心，确信他们的电池已经过充分测试，并符合三星的性能和安全标准。该媒体还暗示，这些电池中的安全芯片可能有助于回收过程。从理论上讲，经过验证的电池将为回收商提供有关电池制造商、使用详情以及其他相关信息的可靠数据。这些细节可以帮助公司选择正确或最高效的回收方法。 —— Androidauthority
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DeepSeek等公司将就AI风险向联合国安理会作简报 据两位知情人士透露，DeepSeek 等公司将于本周就人工智能带来的风险向联合国安理会作简报。眼下，世界各国领导人正齐聚纽约，出席一年一度的联合国大会。 联合国安理会定于周三开会讨论AI与国际安全。几周前，多家AI行业领袖呼吁协调放缓日益强大的AI系统的开发，警告这些系统可能很快将自行改进并脱离人类控制。 知情人士称，DeepSeek以及包括月之暗面在内的其他中国AI企业已受邀发言。DeepSeek创始人梁文锋没有计划出席。相关安排仍可能有变，甚至在最后一刻调整。 —— 凤凰网科技、路透社
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马斯克：旗下公司计划在得州建“超级高铁” 埃隆·马斯克最新表示，旗下的隧道企业“无聊公司”（The Boring Company）计划在美国得克萨斯州开发一条连接奥斯汀、圣安东尼奥的城际隧道，可以想象为“简易版超级高铁”，将两座城市的交通时间从2.5小时压缩至30分钟以下。根据马斯克在社交媒体平台 X 上发表的帖子，拟议的项目将成为马斯克长期以来讨论的超级高铁概念的先导，移动速度将超过200英里/小时。不过，该项目最终能否落地仍是个未知数，“无聊公司” 此前宣发的芝加哥、洛杉矶、纽约隧道项目都没有落地。而且，马斯克没有透露任何政府合作伙伴，也没有表明初步建设是否已经开始。因此，他的帖文可能只是个想法。 —— 财联社、彭博社
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CMF脱离Nothing独立运营 成为印度企业 瑞典华裔企业家、消费电子品牌Nothing联合创始人兼首席执行官裴宇（Carl Pei）正式对外宣布，将旗下主打平价市场的子品牌CMF从原有体系中完全拆分，组建一家由印度资本控股的独立本土企业。这一调整标志着此前逐步推进的印度市场深度本地化战略进入落地阶段。当地时间周一，裴宇在 X 平台发布题为《印度是大势所趋》的公开文章，详细披露了CMF的独立运营方案。拆分完成后的CMF将完全以印度本土企业的身份运行：总部落地印度全境，搭建完全本地化的专属管理团队与独立研发中心，企业控制权由印度资本掌握。而原母公司Nothing总部仍保留该业务板块的部分股份。 —— 电子工程专辑、彭博社
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OpenAI与Anthropic曾讨论互测大模型 据知情人士透露，Anthropic和OpenAI曾考虑签署一份具有法律约束力的协议，以相互对对方的大模型进行压力测试。今年早些时候，这两家公司及其律师团队曾就此计划展开讨论。在该计划中，竞争对手公司可以对彼此最新可用模型进行深度测试，以寻找潜在的风险或安全漏洞。 近来，在顶尖AI实验室之间推行某种形式的同行评审的想法越来越受到关注。而就在上周，埃隆·马斯克建议，美国领先的几家大模型公司，以及部分中国AI公司，应当允许竞争对手进行交叉测试和同行评审。 —— 财联社、The information
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沃尔玛中国调整双业态采购负责人 沃尔玛中国宣布两项核心采购线人事任命，涉及山姆会员商店与沃尔玛商店两大业态。 任命内容显示，现任美国山姆会员商店非食品采购高级副总裁 Sean Jackson 将外派至中国，出任山姆会员商店首席采购官，直接向山姆会员商店业态总裁刘鹏汇报。 与此同时，现任沃尔玛中国副总裁、山姆会员商店非食品采购负责人 Amber Bynum 调任沃尔玛商店首席采购官，向沃尔玛商店业态总裁祝骏汇报，计划10月中旬正式到岗，未来一个月内完成岗位交接。 —— 界面新闻
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日本JCB卡在中国超1800座地铁站实现刷卡过闸 日本信用卡公司JCB发布消息称，已在中国广东省深圳市的地铁实现刷信用卡非接触支付乘车。包括此次新增的地铁站在内，该公司的非接触支付目前可在中国共 1891 座车站使用。JCB International已在深圳地铁启动相关服务。用户可在闸机上进行非接触支付，无需提前购买车票，只需刷一下信用卡或者绑定了信用卡的智能手机，即可乘坐地铁。JCB此前已在中国上海市、北京市和广东省广州市的地铁引入非接触支付，深圳是第4座开通该服务的城市。JCB说：“还支持各城市的机场线，游客也可以便捷使用”。 —— 日经新闻
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Showing the 12 most recent of 849 posts we hold for @xhqcankao. 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.
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
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 18 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.
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.
Telegram’s own answer, not this register’s. When this register asks Telegram’s API what is similar to this channel, this is the list it returns, in the exact order Telegram returns it — never re-sorted by subscribers or by anything else this register measures. The relationship, and the order, are Telegram’s; we record them and date them, and make no claim of our own about which of these channels actually resemble this one.
Read from Telegram’s recommendation API, most recently 12 August 2026. Telegram holds a list like this for a small and growing share of the register — how this is measured, and why most channel pages show nothing here.
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.
This channel appears in 121 seed channels' Telegram-generated recommendation lists in total, of which the 24 where it ranks highest are shown above. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
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 18 September 2026 — this entry's latest reading, not the date you are reading this.
“风向旗参考快讯” (@xhqcankao), 163,238 subscribers as measured 18 September 2026. Telegram Register, tgregister.com/channel/xhqcankao.
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.