阑夕 engagement report
@foxshuo - 172K followers on X
Measured over 23 original posts from a 30-day window, last computed on October 20, 2026.
Engagement
A typical post picks up 183 interactions against 172K followers, an engagement rate of 0.106%. Measured over 23 original posts, its engagement rate beats 60% of 20,444 tracked accounts of a similar size, which puts it in the middle of its size range rather than at either end. Posts are seen about 43K times each, and 0.43% of those impressions turn into an interaction. That is about 24.8% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.1 post a day over the last 30 days, with activity on roughly 77% of days. Most posts go out around 03:00 UTC, and Friday is the busiest day of the week. Of the 23 posts sampled, 13% are part of a thread. The account's strongest tracked post pulled 3.7K interactions, about 20x its own typical post.
Measured over 23 original posts from a 30-day window, last computed on October 20, 2026.
Compared with accounts its own size
阑夕's engagement rate beats 60% of the tracked X accounts closest to it in follower count (20,444 accounts, accounts of similar size (decile 9 of 10)). A percentile is spread evenly by construction, so 50 really is the middle of that group and 90 really is its top tenth.
On engagement per impression rather than per follower it beats 24% of the same group. When those two numbers disagree, the gap is about how far its posts travel rather than how people react to them.
Where this sits in the catalog
At 0.106%, 阑夕 sits above the 25th percentile of the 205,048 accounts in this comparison. That places it in the below the median band, which runs 0.024% to 0.143%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.004% |
| 25th percentile | 0.024% |
| 50th percentile | 0.143% |
| 75th percentile | 0.678% |
| 90th percentile | 2.55% |
| 99th percentile | 82.4% |
This ruler is the whole measured catalog, not a size-matched group: it shows where the raw rate falls across every account we can measure, all of which are large. For a like-for-like comparison, read the size-band percentile above instead. See how the bands are built
Posting timing
This account posts most often around 03:00 UTC, and Friday is its busiest day of the week. The bars below are the catalog-wide pattern, with this account's own busiest slot marked. They do not show how this account performs at each hour: we keep one aggregate per account, not one per hour, so that measurement does not exist in our data.
Show engagement by hour posted, utc as a table
| Hour (UTC) | Vs author median | Posts |
|---|---|---|
| 00:00 UTC | -1% | 89K |
| 01:00 UTC | -2% | 90K |
| 02:00 UTC | -3% | 88K |
| 03:00 UTC | -4% | 94K |
| 04:00 UTC | -5% | 76K |
| 05:00 UTC | -4% | 75K |
| 06:00 UTC | -5% | 86K |
| 07:00 UTC | -5% | 93K |
| 08:00 UTC | -4% | 108K |
| 09:00 UTC | -4% | 124K |
| 10:00 UTC | -3% | 129K |
| 11:00 UTC | -3% | 141K |
| 12:00 UTC | -3% | 154K |
| 13:00 UTC | -3% | 167K |
| 14:00 UTC | -4% | 173K |
| 15:00 UTC | -2% | 176K |
| 16:00 UTC | -3% | 171K |
| 17:00 UTC | -3% | 159K |
| 18:00 UTC | -2% | 149K |
| 19:00 UTC | -2% | 141K |
| 20:00 UTC | -1% | 131K |
| 21:00 UTC | 0% | 116K |
| 22:00 UTC | -2% | 100K |
| 23:00 UTC | -1% | 90K |
Show engagement by day of week as a table
| Day | Vs author median | Posts |
|---|---|---|
| Sunday | +5% | 393K |
| Monday | +1% | 483K |
| Tuesday | -2% | 520K |
| Wednesday | -3% | 472K |
| Thursday | -2% | 430K |
| Friday | -3% | 447K |
| Saturday | +2% | 393K |
Formats this account uses
Its own posting mix on the left, and what each of those formats does across every account we track on the right. Only formats where the effect clears our publish test appear here, so an empty row is a format we could not measure rather than one that does nothing.
| Format | This account | Catalog effect | 95% interval | Accounts behind it |
|---|---|---|---|---|
| Image or video | 0% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 0% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | +15% | +14% to +16% | 32K |
- 0% of this account's sampled posts carry an image or video. Across the catalog, posts with an image or video run 111% above the same accounts' other posts.
- 0% of its posts carry a link off X. Across the catalog, posts with an outbound link run 41% below the same accounts' other posts.
- Its average post runs 503 characters, which falls in the over 280 characters band. Across the catalog, posts over 280 characters run 15% above the same accounts' other posts.
These are catalog-wide differences applied to this account's own posting mix, not a measurement of how each format performs for this account specifically. We keep one median per account, not one per format per account, so the second thing is not something this data can tell you.
Best tweets
- Sep 3, 202620x their median
这是什么性癖，有懂的吗？ https://t.co/RLfjRGFGWy
- Oct 16, 20263.6x their median
我今天讲句大实话，可能说得有点过头。大家看特斯拉新 Roadster，火箭推进、超强加速，很多人觉得性能炸裂。但按照华为的质量标准，这台车一台都发不出厂。 华为有着极其严苛的整车验证体系，达不到标准，任何人都没法放行，就算是我，也不能签字出厂。 很多人觉得，开 Roadster，动力拉满，在公共道路炫技很酷。我想说，公共道路上悬浮喷气推进，是最愚蠢的行为！ 不要一味追逐纸面极速、零百加速。尊界这套底盘、乾崑 ADS，我们所有的性能调校，核心目标是可控、是安全。性能，要在专业赛道释放；公共道路，承载的是所有路人的生命安全。 质量才是最大的豪华，安全才是一台高端车的根基。再强的动力、再炫的硬件，如果整车验证、安全冗余不达标，根本没有资格流向用户。
- Sep 29, 20263.2x their median
我有个朋友在做一件很取巧的事情，他开了一家AI短剧公司，经营得还可以，今年开始，他委托第三方找了很多曾经火过的「山寨明星」，也就是撞脸明星的普通素人，用很低的价格和他们签形象授权协议，就是独家买断他们的脸作为训练原型，最后就能用到非常接近对应明星形象、但在来源层又完全合规的AI角色，毕竟法律再怎么保护明星的肖像权，也不可能禁止别人长得像明星。 他说先把这批AI角色用在自己的剧集里跑跑看，如果效果好，还可以向其他短剧公司分销这批形象版权。 我听得一愣一愣的。
- Sep 7, 20263.0x their median
野村证券的中国互联网夏季研报写了一些很关键的数据，大部分出自Quest Mobile： - 抖音的月均使用时长有史以来第一次超过了微信，成为中国人最耗时间的App，抖音的日活用户（7.14亿）低于微信（9.31亿），这意味着每个活跃用户投入在抖音的时间要远高于微信； - 在中国月均使用时长排名前20的App里，字节独占5席，依次是抖音、抖音极速版、红果短剧、今日头条和番茄小说，分走了中国网民35%的使用时长，而腾讯占到4席，分别是微信、搜狗输入法、王者荣耀、腾讯新闻，但加起来只分走了24%的时长占比； - 红果短剧的日活用户达到1.68亿，比「爱优腾芒」四大长视频平台加起来还多⋯⋯而且随着假期到来，红果短剧的增长甚至还没放缓，同比高达107%，而「爱优腾芒」的日活用户全都出现了两位数以上的下降，无一幸免； - 在线音乐市场也在被字节系产品蚕食，汽水音乐和番茄音乐的日活用户分别增长70%和37%，除了网易云音乐守住基本盘没有崩掉以外，QQ音乐、酷狗音乐、酷我音乐均在不同程度的流失用户； - 小红书的日活用户涨了6%，可以理解为是世界杯直播版权换来的增量，值不值就看内部如何判断了，但社交赛道总体来说还是下行的，微博和QQ的日活用户和使用时长都在往下掉； - AI应用赛道，豆包的1.68亿日活依然断崖式领先，远远甩开日活3100万的DeepSeek和日活2800万的千问，不过从日均使用时长来看，中国仍然没有任何一款AI应用能突破20分钟，最高的是DeepSeek，16.5分钟，环比下降； - 钉钉日活7700万，企微日活7200万，飞书日活1000万，但用户的日均使用时长是反过来的，飞书14.8分钟，企微12.4分钟，钉钉9.9分钟，这应该是它们最后一次被单独分类统计了，整条赛道都会被AI办公给顶替掉； - 携程、去哪儿、飞猪三大OTA平台的日活用户全都出现了下降，这在暑假这个旅游旺季不太应该出现，说明选择出去玩的人在变少，对照来看，百度和高德的日活用户也在下降； - 其他主流App方面，拼多多的日活用户再次反超淘宝，美团的日活用户微涨，但使用时长不增反降，百度的日活用户暴跌21%，Boss直聘成了这个暑期档除字节系之外的最大赢家，日活用户大涨15%。
- Sep 16, 20262.9x their median
YouTube上的中文政论节目，如果柴静是90分，第二名——不管是谁——大概是15分左右。
- Sep 15, 20262.6x their median
绷不住了，看到北京互联网法院分享了一个案子，起诉者说17岁的女儿在直播里打赏了300多万人民币，要求平台未成年退款。 但在查证消费流水的过程里，平台发现三个涉案账号总共打赏了560万，法官就很奇怪了，这种情况一般来说只有多报的，很少见到往少了报的，而且一少就是200多万，也太心大了吧。 而且起诉者的情绪很反常，一点都不急，爸爸全程没有出面，妈妈平静理性的表示，自己没管好孩子，肯定有错，但平台还是应该酌情退款，甚至在起诉期间，那些账号还在继续打赏，又花出去了十几万。 继续深挖才发现，这三个账号，打赏行为分布在全天时段，没有上课、休息、睡觉的痕迹，而且登录IP也老在变化，而且还藏了第四个账号，是父亲实名注册的，也打赏了90万，把总金额提高到了650万。 最后的真相是，这一家三口，父亲、母亲、女儿全都沉迷于大额打赏，各有各的主播在养，甚至女儿曾在给主播打赏冲榜时触发了消费限制，是父亲来刷脸帮忙解除的⋯⋯ 在法官的视角里，这个家庭环境还是挺扭曲的，有钱是有钱，但金钱观很不健康，在后悔花钱太上头后，是全家一起商量好了，把打赏金额全都推到女儿一个人头上，走未成年退款这个路子，也教她怎么撒谎应对法庭问询。 「我常跟同事说，这类案子审到最后，看见的都是同一个画面：一家人坐在沙发上，各自对着发光的小屏幕，谁也不看谁。」
- Sep 16, 20262.3x their median
这个构图…… https://t.co/HQIgAW3Ht1
- Sep 13, 20262.2x their median
晚点LatePost那期讲模型蒸馏的播客其实还蛮有料的，比如字节的部分。 张一鸣不让Seed蒸馏，同时允许暂时落后，是有野心和抱负的，以字节的体量而言，必然要和万亿美金级别的巨头平起平坐。 所以张一鸣不接受蒸馏这种无限逼近教师模型而无法真实超过的路线，虽然部分从业者并不认同。 因为理论上，蒸馏只是训练模型的手段之一，你完全可以同时也在其他方面做出创新，蒸馏出90分，在别的地方再拿20分，加起来未必不能超过教师模型。 只是张一鸣担心的是，这会带来组织上的依赖和代价，「他可能不是最懂技术的人，但他大概率是最懂人性的人。」 果不其然，在张一鸣这么公开表态后，Seed很快就又走了几个人，站在这些人的角度，也有很充足的理由，这一代年轻人的职业生涯，是有限的，字节耗得起，但我耗不起，在我最黄金的年龄，如果不能在字节这边尽快拿出自己的代表作，会非常亏。 而蒸馏就是最主流的速胜打法，只要上了前沿模型的贡献者名单，身价就会不讲道理的暴涨，既然字节在短期内给不了这个机会，就别怪良禽择木而栖了。 字节也在组织上设法克服不蒸馏的困难，包括成立了和Seed同级的数据部门，解决高质量数据的来源问题。
- Sep 11, 20262.2x their median
锐评一下Anthropic今天发布报告里关于蒸馏指控的部分，尽量讲真话。 蒸馏模型这个事情，分为事实判断和价值判断两个部分。 在事实判断部分，国产模型的态度，基本看不到明确否认的，这个很容易理解，因为它是真的会留下客观证据，从业者没必要为了一份工作，搭上自己一辈子的职业信誉。 主流的解释口径，在于价值判断，就是让教师模型言传身教这件事情本身，作为行业普遍的学习手段，是没问题的，所谓的禁止蒸馏，只不过是公司的用户协议，而无法上升到法律层面。 再说了，前沿模型在训练时，也一定从互联网上抓取了你我的生产内容，你我这样的人，有机会表示拒绝吗？表示了又能怎么样呢？ 所以后来，Anthropic也在改变描述，在蒸馏前面加上了「工业级」这个定语，用以和正常合理的蒸馏行为作出区分，但总体上，仍然是用户协议的性质。 既然是用户协议，那就遵循猫鼠游戏的玩法，你可以封号，我也能起号，看谁手更快喽？ 而且蒸馏并不是没有害处的，过于依赖蒸馏，就会锁死模型智能的上限，因为学生模型是不可能超过老师模型的，这是物理规律，所以在蒸馏之外，国产模型也在花大力气去做架构创新。 不过Anthropic的报告，倒是意外回答了关于今年7月短暂出现在OpenCode里的DeepSeek神秘灰测模型的都市传说，这个很有意思。 应该还有不少人记得，7月中旬，有人发现在OpenCode里调用DeepSeek的API完成任务时，会偶尔抽到一个能力明显超过V4 Preview的模型，前端效果足以媲美Fable 5。 你们现在去B站限定那段时间搜索，还能看到上百条录屏，全是各种炸裂体，坚信这就是DeepSeek憋的大招，发布出来即可成为中国第一个与Fable 5平起平坐的新模型，也就是大家期待的V4 Pro。 当时技术社区里有人质疑，因为实在和Claude的模型特征太像了，这是不是DeepSeek把一部分请求路由到了Claude完成，还被各种嘲讽： 「什么？你是说梁圣，收了V4 Preview的费率，给我用满血的Fable 5吗？义父！容我一拜！」 结果最简单的直觉反而是真的，因为8月DeepSeek-V4 Pro发布之后，并没有复现灰测模型的能力，甚至一个月不到就被自家的V4.1 Flash给斩杀了⋯⋯ 虽然至今还有人对那几天的灰测模型念念不忘，认为这是梁圣在藏，有核弹级的好东西就是不拿出来给大伙用——所以才说已经成了都市传说——Anthropic的报告细节实际上交叉验证了这个说法，大部分蒸馏交互都是在7月份发生的。 这当然不是DeepSeek真的在做慈善，OpenCode是一个编程平台，用户交互的都是真实的高价值任务，在这个过程会产生长程Agent轨迹，非常适合抽取原本被隐藏的思维链，所以贴钱给用户发福利，是有确定回报的。 真正比较危险的，是在Anthropic明牌反华的立场下，还通过第三方中转站来做这样的蒸馏，敏感数据流向Anthropic之后，难保它不会反手交给美国情报部门。 而且中转站掺水也是无法控制的，晚点LatePost前段时间的一期播客就讲到了，有家国产模型在中转站可劲儿的蒸了好久，最后发现海外模型被节省成本的中转站偷偷替换成了自家的模型，相当于一直是在自己蒸自己⋯⋯ 🤣🤣🤣
- Sep 4, 20262.2x their median
韩国手游「棕色尘埃2」的发布会真是限制级的…… https://t.co/Lzp2CS7ZIu
Ranked by total interactions across everything we have tracked for this account, which is a longer history than the 30-day window the rates above use. The multiple compares each post to this account's own median.
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Reading these numbers
A typical post picks up 183 interactions against 172K followers, an engagement rate of 0.106%. Measured over 23 original posts, its engagement rate beats 60% of 20,444 tracked accounts of a similar size, which puts it in the middle of its size range rather than at either end. Posts are seen about 43K times each, and 0.43% of those impressions turn into an interaction. That is about 24.8% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.1 post a day over the last 30 days, with activity on roughly 77% of days. Most posts go out around 03:00 UTC, and Friday is the busiest day of the week. Of the 23 posts sampled, 13% are part of a thread. The account's strongest tracked post pulled 3.7K interactions, about 20x its own typical post.
- What is 阑夕's engagement rate on X?
- 阑夕 (@foxshuo) has an engagement rate of 0.106%, based on the median interactions across 23 original posts from the last 30 days against 171,778 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.106%, 阑夕 sits above the 25th percentile of the 205,048 accounts in this comparison. Those comparison accounts are all large ones, because our scanning cadence is weighted towards big accounts, so this is a ranking among peers of similar scale rather than a ranking across X.
- Does @foxshuo have real engagement?
- Its engagement rate beats 60% of the tracked X accounts closest to it in follower count (20,444 accounts), which puts it in the middle of its size range group. Ranking inside a size band matters because engagement rate falls as accounts grow, so a raw rate would mostly re-measure the follower count. It is a starting point for a look at follower quality, not a verdict on it.
- When does @foxshuo post?
- Most posts go out around 03:00 UTC, and Friday is its busiest day, at roughly 1.13 posts per day across the measured window.