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Channel
@danfeng2
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Posts edited after publishing · Posts recorded as deleted · Citations · Handles named that no longer answer · Cite this entry
6,761subscribers
+2,641 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 3,162–10,000.
| Telegram ID | -1002764001836 |
|---|---|
| Type | Channel |
| Username | @danfeng2 |
| Description | 🌐 CF 优选 IP / 中转 IP 数据分享 🚀 公益代理订阅 · 节点更新公告 🤖 免费 AI 大模型 API 与实用教程 📡 网络资讯 · 开源项目推荐 💬 群内回复「订阅」获取最新链接 |
| Created | Between 1 June 2025 and 30 September 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 12 November 2026 |
| Measurements held | 27 |
| Confirmed unchanged | 1 time, most recently 12 November 2026 |
| On Telegram | t.me/danfeng2 |
Technology — 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 13 September 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 the other topics.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 12 Nov 2026, 22:47 | 6,761 | +158 |
| 9 Nov 2026, 00:21 | 6,603 | +157 |
| 5 Nov 2026, 08:06 | 6,446 | +125 |
| 2 Nov 2026, 02:29 | 6,321 | +114 |
| 30 Oct 2026, 12:16 | 6,207 | +129 |
| 27 Oct 2026, 04:37 | 6,078 | +82 |
| 24 Oct 2026, 12:59 | 5,996 | +137 |
| 21 Oct 2026, 07:48 | 5,859 | +118 |
| 18 Oct 2026, 03:57 | 5,741 | +116 |
| 15 Oct 2026, 10:35 | 5,625 | +95 |
| 12 Oct 2026, 01:21 | 5,530 | +367 |
| 5 Oct 2026, 08:14 | 5,163 | +236 |
| 26 Sept 2026, 22:41 | 4,927 | +138 |
| 18 Sept 2026, 02:00 | 4,789 | +83 |
| 13 Sept 2026, 17:40 | 4,706 | +105 |
| 10 Sept 2026, 07:19 | 4,601 | +94 |
| 5 Sept 2026, 10:15 | 4,507 | +42 |
| 1 Sept 2026, 07:05 | 4,465 | +30 |
| 29 Aug 2026, 01:03 | 4,435 | +22 |
| 26 Aug 2026, 07:03 | 4,413 | first reading |
44 posts held, back to 9 June 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 14 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. It is computed over the 16 of 17 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 11 November 2026 |
|---|---|
| Posts held | 44 (9 June 2026 – 11 November 2026) |
| Views total | 45,440 |
| Reactions total | 165 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 13 Nov 2026, 03:13 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 13 November 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.
285 reactions across 36 posts, in 14 distinct kinds. The most used accounts for 48.8% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 139 | 48.8% | |
| 👍 | 101 | 35.4% | |
| 🔥 | 9 | 3.16% | |
| 🤡 | 9 | 3.16% | |
| 🥰 | 9 | 3.16% | |
| 😱 | 4 | 1.40% | |
| 👏 | 3 | 1.05% | |
| 👎 | 2 | 0.702% | |
| 💩 | 2 | 0.702% | |
| 🕊 | 2 | 0.702% | |
| 🤮 | 2 | 0.702% | |
| 🏆 | 1 | 0.351% | |
| 😁 | 1 | 0.351% | |
| 😈 | 1 | 0.351% |
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 36 of the 44 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 285 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 44 most recent posts we hold, published 9 June 2026 to 11 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.
Telegram’s own ‘edited’ marker: 6 of 17 posts held from the last 30 days (35.3%) 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).
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🚀 中国移动 Cloudflare 特殊线路扫描器 用于中国移动家庭宽带环境,从 Cloudflare 官方 IPv4 地址中筛选特殊线路候选 IP。 📌 主要功能 🎲 支持随机扫描 🔍 支持全量扫描 ⏯️ 全量扫描支持断点续扫 ⚠️ 使用注意 仅适用于中国移动家庭宽带网络,不适用于手机移动数据网络,也不建议直接用于其他运营商网络。
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此前所有被误判封禁的账号已处理完毕。 如有遗漏,请私聊反馈。
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WebProxy
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🥚 赛博领鸡蛋|免费 Muse.ai 账号 🎁 免费领取 Muse.ai 账号,并且获取额外词元! ━━━━━━━━━━━━━━ 一、免费领取 Muse.ai 账号 🤖 领取机器人: 1️⃣ 点击链接,关注指定频道 2️⃣ 点击机器人下方按钮(claim xxx xxx),领取免费 Muse 账号 3️⃣ 领取后会获得一个邮箱和一个验证码链接 4️⃣ 打开 Muse.ai,输入邮箱并发送验证码 5️⃣ 打开领取到的链接,获取验证码并完成登录 📌 建议换绑自己的邮箱: 登录后依次进入: 左下角横杠 → 设置 → 通用 → Meta 账户 → 邮箱→ 邮箱 → Add or edit contact info 按照页面提示添加或更换为自己的邮箱。 ━━━━━━━━━━━━━━ 二、免费刷邀请次数 登录 Muse.ai 后,进入主页点击「邀请」,获取自己的邀请码。 🤖 刷邀请机器人: 🎁 获取规则: 首次完成验证:获得 …
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⚠️ 订阅域名异常通知 *.chinat.eu.org 已遭遇 DNS 污染。 📌 获取或更新订阅时,需通过代理再导入。
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已恢复。 已恢复。 已恢复。 再次重申,不要短时间内多次在群中触发订阅,否则会被机器人拉黑!
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改动代码,触发代码审查,1101了 晚点看看能不能修复
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这两天北京开会,GFW探测功率拉满了,对海外ip不是直接封锁ip, 而是墙TCP端口,阻断被检测到翻墙的海外ip所有端口的TCP连接,而ICMP(Ping) 和UDP则正常。之前4月份中国移动蜂窝移动出现过类似现象,可能是之前是测试,现在大范围应用。
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CF大善人收费了,SaaS面板删库跑路 用户记录不会删除,域名会删除 随机下次开放 总计限额90个域名
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Showing the 12 most recent of 44 posts we hold for @danfeng2. 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.
@danfeng2 edited 1 post after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.
An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.
We recorded 3 posts on @danfeng2 as deleted — posts this register held that were missing from the channel’s public page on two separate reads, taken from different network addresses at least an hour apart.
A deletion is not wrongdoing. This register can see that a post it held is no longer on the channel’s public page, and when — not why. Expired ad placements, reposts, rotating links and corrections all look the same. This is a count of recorded detections, not an exact total: it misses deletions we could not see, because only a post we held and later re-read inside the page can be seen to go, and it may include a small number of wrong records. How this is measured.
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.
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.
@danfeng2 named 1 handle that resolve to nothing today. That is a fact about the reference, not necessarily a fact about the handle’s history — see the two groups below.
Most of these may never have existed as a live channel at all. A handle a channel names can be a typo, an aspirational name nobody registered, or a channel that was already gone before this one ever mentioned it. Unless a row below is marked evidenced, all we know is that it references a handle that is not a live channel today — not that anything “died”. How this is measured.
References a handle that is not a live channel — we have no record it ever was one.
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.
“DanFeng 分享交流” (@danfeng2), 6,761 subscribers as measured 12 November 2026. Telegram Register, tgregister.com/channel/danfeng2.
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.