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徐晓冬 北京格斗狂人 engagement report

@Xuxiaodong3 - 471K followers on X

Measured over 12 original posts from a 30-day window, last computed on October 25, 2026.

Engagement

Middle of its size range
Per follower
0.063%
of 471K followers
Per impression
0.557%
53K views on a typical post
Reach
11.3%
of its followers see a post
Typical post
297
interactions (median)
Saved
0.015%
8 bookmarks on a typical post
Posting rate
0.4/day
active 27% of days
Peak time
06:00 UTC
Thursday

A typical post picks up 297 interactions against 471K followers, an engagement rate of 0.063%. Measured over 12 original posts, its engagement rate beats 63% 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 53K times each, and 0.557% of those impressions turn into an interaction. That is about 11.3% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.4 posts a day over the last 30 days, though only 27% of days saw any activity at all. Most posts go out around 06:00 UTC, and Thursday is the busiest day of the week. Of the 12 posts sampled, 92% carry an image or video. The account's strongest tracked post pulled 4.2K interactions, about 14x its own typical post.

Measured over 12 original posts from a 30-day window, last computed on October 25, 2026.

Compared with accounts its own size

徐晓冬 北京格斗狂人's engagement rate beats 63% of the tracked X accounts closest to it in follower count (20,444 accounts, accounts of similar size (decile 10 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 33% 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 0.063%, 徐晓冬 北京格斗狂人 sits above the 25th percentile of the 204,583 accounts in this comparison. That places it in the below the median band, which runs 0.024% to 0.143%.

p100.004%
p250.024%
p50 (median)0.143%
p750.677%
p902.55%
p9982.4%
Engagement rate as a share of followers, across the 204,583 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 22,891 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 percentile0.004%
25th percentile0.024%
50th percentile0.143%
75th percentile0.677%
90th percentile2.55%
99th percentile82.4%

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 06:00 UTC, and Thursday 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: 06:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 111%Busiest hour: 06:00 UTC
Show engagement by hour posted, utc as a table
Engagement by hour posted, UTC
Hour (UTC)Vs author medianPosts
00:00 UTC-1%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 UTC0%116K
22:00 UTC-2%100K
23:00 UTC-1%90K
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: Thursday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 111%Busiest day: Thursday
Show engagement by day of week as a table
Engagement by day of week
DayVs author medianPosts
Sunday+5%393K
Monday+1%483K
Tuesday-2%520K
Wednesday-3%472K
Thursday-2%430K
Friday-3%447K
Saturday+2%393K
See what moves engagement across the whole catalogWhat counts as a good engagement rate at this size

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.

This account's posting mix compared with catalog-wide effects
FormatThis accountCatalog effect95% intervalAccounts behind it
Image or video92% of posts+111%+108% to +115%34K
Outbound link0% of posts-41%-42% to -40%32K
Typical length--3%-3% to -2%54K
  • 92% 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 97 characters, which falls in the 80 - 180 characters band. Across the catalog, posts of 80 to 180 characters run 3% below 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 2, 202614x their median

    是的,他安全落地了。祝老师 新的生活新的开始幸福安康 https://t.co/dZhNOWvh2m

    3.0K861.1K29599K viewsView on X
  • Oct 22, 20268.9x their median

    今天我为“平安北京”做出贡献!马上两会了这么敏感的时期,此人在我家跟踪我3-4天,今天被我抓住! 在北京中心城区内居然有这样的犯罪嫌疑人!我是徐晓冬!光明正大!强壮💪牛逼!我不会自杀!记住!我不会自杀。邪恶的人,来一个收拾一个! https://t.co/t3NOC7KrNr

    2.0K15451513501K viewsView on X
  • Oct 22, 20264.4x their median

    报警🚔,报了3次警!警察👮同志到了,把这位犯罪嫌疑人带走了。(我已经预料到了对他询问后的结果……)我做的就是:不能让坏人们肆无忌惮!不能让坏人们欺负到家门口! 记住:首先自己要有个强壮的身体!第一时间保护只有靠自己!!!! https://t.co/YONLduqkPf

    1.1K591877191K viewsView on X
  • Sep 3, 20264.0x their median

    期待星星之火🔥 https://t.co/BfVU8QzyQq

    960162097107K viewsView on X
  • Jul 4, 20263.7x their median

    正式向上海教育局,复旦大学纪委投诉沈逸教授 公然侮辱同胞为“汉奸” 。教育局正式受理, 我们知道很可能没什么后续,或者惩罚不痛不痒,但我们必须要坚持!因为这是我们的态度!在这里混沌的环境中,我们要坚持我们的态度 司马南 沈逸 才是真正的害群之马 我的环境 我只能说到这里~感谢上海徐哥 https://t.co/nZYWFuLSvK

    870441875115K viewsView on X
  • Aug 23, 20263.7x their median

    今天8月23日北京时间中午12点,中国第一战地记者唐师曾 唐老师走了…… 2019年10月,我的必图拳馆走进来一位老大哥,张嘴就说,徐晓冬我要当你最大年纪的徒弟可以吗…………,之后7年,我反而从唐老师那里学到了很多知识。 今年4月我去医院看望唐老师,又说了很多很多,唐老师走好🙏 https://t.co/JKvoO0S5xY

    830292295124K viewsView on X
  • Aug 28, 20262.5x their median

    拆不完的…… https://t.co/X7joYFhNIK

    6891425287K viewsView on X
  • Oct 2, 20262.2x their median

    巴勒斯坦🇵🇸!是巴勒斯坦🇵🇸!他妈的40%领土面积是废墟的 巴勒斯坦🇵🇸!照顾球~也不能踢成这样吧!姥姥的,脸不要脸,这次连屁股都不要了…………0:5!0:5!懂足球⚽️的都懂我说的意思!1:主场,2:国际A级赛事!3:0:5!4:输给巴勒斯坦🇵🇸!脸和屁股都不要了~~~~~~~ https://t.co/SZO6bFJwpB

    476381431172K viewsView on X
  • Oct 22, 20261.6x their median

    告诉它们:不要得寸进尺~外地跟踪,网络跟踪,现在都跟踪到家门口了~ 哪位大神出的主意?太低级了吧~ 在北京中心区域 马上要开大会,这么敏感的时期,跟踪人民~还被人家发现了~警察也来了,人也带走了,整个小区都知道了!太丢人了! 太丢人了~ https://t.co/i0fWF3K9FU

    34222119059K viewsView on X
  • Oct 9, 20261.6x their median

    我3年前就骂华为余承东 涉嫌 虚假宣传 现在尊界800出事只是其中之一 还会有 等着 https://t.co/wnEracI47s

    3921952165K 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 297 interactions against 471K followers, an engagement rate of 0.063%. Measured over 12 original posts, its engagement rate beats 63% 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 53K times each, and 0.557% of those impressions turn into an interaction. That is about 11.3% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.4 posts a day over the last 30 days, though only 27% of days saw any activity at all. Most posts go out around 06:00 UTC, and Thursday is the busiest day of the week. Of the 12 posts sampled, 92% carry an image or video. The account's strongest tracked post pulled 4.2K interactions, about 14x its own typical post.

What is 徐晓冬 北京格斗狂人's engagement rate on X?
徐晓冬 北京格斗狂人 (@Xuxiaodong3) has an engagement rate of 0.063%, based on the median interactions across 12 original posts from the last 30 days against 470,707 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.063%, 徐晓冬 北京格斗狂人 sits above the 25th percentile of the 204,583 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 @Xuxiaodong3 have real engagement?
Its engagement rate beats 63% 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 @Xuxiaodong3 post?
Most posts go out around 06:00 UTC, and Thursday is its busiest day, at roughly 0.4 posts per day across the measured window.

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