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财经数据库 engagement report

@caijingshujuku - 374K followers on X

Measured over 39 original posts from a 30-day window, last computed on September 1, 2026.

Engagement

Bottom quarter for its size
Per follower
0.009%
of 374K followers
Per impression
0.17%
20K views on a typical post
Reach
5.35%
of its followers see a post
Typical post
34
interactions (median)
Saved
0.02%
4 bookmarks on a typical post
Posting rate
1.9/day
active 17% of days
Peak time
14:00 UTC
Saturday

A typical post picks up 34 interactions against 374K followers, an engagement rate of 0.009%. Measured over 39 original posts, its engagement rate beats 18% of 3,862 tracked accounts of a similar size. That is a reason to look at how the audience behaves - reply depth, saves, whether the followers are recent - rather than a conclusion about it on its own. Posts are seen about 20K times each, and 0.17% of those impressions turn into an interaction. That is about 5.35% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.9 posts a day over the last 30 days, though only 17% of days saw any activity at all. Most posts go out around 14:00 UTC, and Saturday is the busiest day of the week. Of the 39 posts sampled, 56% carry an image or video, 15% are part of a thread and 41% link out. The account's strongest tracked post pulled 7.5K interactions, about 221x its own typical post.

Measured over 39 original posts from a 30-day window, last computed on September 1, 2026.

Compared with accounts its own size

财经数据库's engagement rate beats 18% of the tracked X accounts closest to it in follower count (3,862 accounts, accounts of similar size (decile 6 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 9% 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 0.009%, 财经数据库 sits above the 10th percentile of the 37,459 accounts in this comparison. That places it in the bottom 25% band, which runs below 0.012%.

p100.002%
p250.012%
p50 (median)0.081%
p750.438%
p902.10%
p99159.8%
Engagement rate as a share of followers, across the 37,459 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 106,523 times apart and a linear axis would flatten everything below the median into a single point.
Show the percentile table
Engagement rate percentiles
PercentileEngagement rate
10th percentile0.002%
25th percentile0.012%
50th percentile0.081%
75th percentile0.438%
90th percentile2.10%
99th percentile159.8%

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 14:00 UTC, and Saturday 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.

Engagement by hour posted, UTCTwenty-four bars, one per UTC hour. Each bar shows how posts published in that hour compare with their own authors' median engagement. Bars above the centre line ran higher than the median, bars below ran lower. A marker flags Busiest hour: 14:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 6%Busiest hour: 14:00 UTC
Show engagement by hour posted, utc as a table
Engagement by hour posted, UTC
Hour (UTC)Vs author medianPosts
00:00 UTC-1%52K
01:00 UTC-2%53K
02:00 UTC-3%51K
03:00 UTC-4%55K
04:00 UTC-6%44K
05:00 UTC-4%43K
06:00 UTC-4%49K
07:00 UTC-5%53K
08:00 UTC-4%62K
09:00 UTC-3%71K
10:00 UTC-2%74K
11:00 UTC-3%81K
12:00 UTC-2%89K
13:00 UTC-2%97K
14:00 UTC-3%100K
15:00 UTC-2%104K
16:00 UTC-4%101K
17:00 UTC-3%94K
18:00 UTC-1%87K
19:00 UTC-2%82K
20:00 UTC-1%77K
21:00 UTC-1%68K
22:00 UTC-1%59K
23:00 UTC-2%53K
Engagement by day of weekSeven bars, one per weekday, Sunday first. Each bar shows how posts published on that day compare with their own authors' median engagement. Bars above the centre line ran higher than the median, bars below ran lower. A marker flags Busiest day: Saturday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 5%Busiest day: Saturday
Show engagement by day of week as a table
Engagement by day of week
DayVs author medianPosts
Sunday+5%236K
Monday0%298K
Tuesday-3%295K
Wednesday-1%255K
Thursday-1%249K
Friday-3%257K
Saturday+3%231K
See what moves engagement across the whole catalogWhat counts as a good engagement rate at this size

Best tweets

  • May 1, 2026221x their median

    刚刚,成都大献忠事件,死伤惨重。 成都高新区天府四街, 有人利用汽车无差别撞人, 估计死亡人数超过了 11 人, 现场很惨烈, 很多视频已经被封了。 凶手撞人后提刀下车准备砍人! 这几个视频是现场最全的 https://t.co/H6v1YWAdxG

    5.3K7411.4K812.2M viewsView on X
  • Aug 28, 202631x their median

    大灾当前,解放军摆拍小分队再次惨烈翻车!全网嘘声一片…… https://t.co/qgySSA0J4e

    841841316375K viewsView on X
  • Aug 29, 202629x their median

    西藏泥石流三天后,中国救援队终于抵达了现场…… 搜救方式原始得让人尴尬! 以为人是泥鳅,在泥浆下能活3天?还能发声? 失联的近600人算是彻底没戏了! 反观泥泊尔救援效率非常高! https://t.co/eWg2t1FdPq

    718881922359K viewsView on X
  • Aug 29, 202616x their median

    这个当兵的无耻行为,遭到全体网友阳阳!太爽了 https://t.co/wyKnqXTgQF

    44325680352K viewsView on X
  • Aug 30, 202615x their median

    那些表明中国无法逃避对尼泊尔洪灾责任的理由 1. 中国是第一个收到警告的一方。洪水发生在西藏吉隆,之后约45分钟才冲向下游的尼泊尔社区。这足够的时间来对邻国实施警告措施。 2. 尼泊尔没有收到有效的警告。在一场跨越边境的灾害中,几分钟的时间也能拯救许多生命。中国有45分钟的时间采取行动,这段时间足以决定是疏散民众还是酿成大规模死亡悲剧。 3. 最初,中国将责任归咎于一場地震。然而,随后美国地质调查局(USGS)得出结论,地震信号正是源于冰湖和岩石的巨大崩塌。 4. 中国正在剧烈改变这一地区。高速公路、铁路、大坝和定居点正在穿过地球上最脆弱且地震活动最强烈的山系之一进行建设。 5. 中国科学家已警告北京。他们已识别出不稳定的山坡、脆弱的地质结构以及连锁崩塌的风险。然而,建设活动仍在继续。 6. 中国隐瞒了灾害的规模。中国媒体最初仅强调有少数确认死亡案例,而在西藏仍有数百人失踪,边境地区的破坏程度已显而易见。中国被指控试图掩盖此事,类似于该国被认为在2019年11月隐瞒COVID-19疫情,通过审查网络信息。 中国需要公布监测数据、警告时间线以及环境影响评估报告;同时解释其基础设施是否加剧了破坏程度,而不是发布宣传视频,展示中国人民解放军(PLA)士兵姗姗来迟抵达现场。 尼泊尔值得获得证据、透明度和问责制。喜马拉雅山脉不承认政治边界。但责任也不能仅仅因为被隐藏在一条边境线后就消失。

    308391416182K viewsView on X
  • Aug 30, 20269.1x their median

    女博主无意拍下的视频,成为关键证据!比县城还繁华的吉隆镇,到底死了多少人? https://t.co/cijDdI8U0P

    2354430056K viewsView on X
  • Aug 30, 20267.8x their median

    习再引众怒!不去吉隆反带彭丽媛出国萧洒!身体不对劲太明显了….. https://t.co/PQkRPJTS2C

    18814611115K viewsView on X
  • Aug 31, 20264.0x their median

    现场突发! 外国摄影师两次靠近习近平, 被保镖粗鲁拉开! 国际哗然! https://t.co/FiRsvwyK8B

    98732058K viewsView on X
  • Aug 30, 20263.7x their median

    中国爆红:中国视频博主记录了尼泊尔-西藏口岸和道路崩塌前的最后时刻。 在这系列视频中,这位女孩表示,她在西藏前往尼泊尔旅行,并在返回中国前,正好赶在可怕的冰崩引发的山洪前。她仍清晰记得口岸女工作人员在护照上盖章时的微笑,以及她在路上遇到的那些司机和便利店售货员的友好。他们所有人可能都已经没能幸存。

    101169140K viewsView on X
  • Aug 28, 20263.4x their median

    抖音审查员都不工作了? 这样的视频都能放了!!! https://t.co/xDmX1gS6BP

    951210051K viewsView on X

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 34 interactions against 374K followers, an engagement rate of 0.009%. Measured over 39 original posts, its engagement rate beats 18% of 3,862 tracked accounts of a similar size. That is a reason to look at how the audience behaves - reply depth, saves, whether the followers are recent - rather than a conclusion about it on its own. Posts are seen about 20K times each, and 0.17% of those impressions turn into an interaction. That is about 5.35% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.9 posts a day over the last 30 days, though only 17% of days saw any activity at all. Most posts go out around 14:00 UTC, and Saturday is the busiest day of the week. Of the 39 posts sampled, 56% carry an image or video, 15% are part of a thread and 41% link out. The account's strongest tracked post pulled 7.5K interactions, about 221x its own typical post.

What is 财经数据库's engagement rate on X?
财经数据库 (@caijingshujuku) has an engagement rate of 0.009%, based on the median interactions across 39 original posts from the last 30 days against 374,266 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.009%, 财经数据库 sits above the 10th percentile of the 37,459 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 @caijingshujuku have real engagement?
Its engagement rate beats 18% of the tracked X accounts closest to it in follower count (3,862 accounts), which puts it in the bottom quarter for its size 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 @caijingshujuku post?
Most posts go out around 14:00 UTC, and Saturday is its busiest day, at roughly 1.9 posts per day across the measured window.

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