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FlyOverChina engagement report

@FlyOverChina - 644K followers on X

Measured over 11 original posts from a 30-day window, last computed on September 2, 2026.

Engagement

Bottom quarter for its size
Per follower
0.001%
of 644K followers
Per impression
0.614%
1.1K views on a typical post
Reach
0.18%
of its followers see a post
Typical post
7
interactions (median)
Saved
0%
0 bookmarks on a typical post
Posting rate
0.37/day
active 30% of days
Peak time
08:00 UTC
Wednesday

A typical post picks up 7 interactions against 644K followers, an engagement rate of 0.001%. Measured over 11 original posts, its engagement rate beats 10% of 6,874 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 1.1K times each, and 0.614% of those impressions turn into an interaction. That is about 0.177% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.37 posts a day over the last 30 days, though only 30% of days saw any activity at all. Most posts go out around 08:00 UTC, and Wednesday is the busiest day of the week. Of the 11 posts sampled, 100% carry an image or video. The account's strongest tracked post pulled 30 interactions, about 4.3x its own typical post. Recurring topics include #chinatravel, #flyoverchina, #gansu.

Measured over 11 original posts from a 30-day window, last computed on September 2, 2026. Recurring tags: #chinatravel, #flyoverchina, #gansu.

Compared with accounts its own size

FlyOverChina's engagement rate beats 10% of the tracked X accounts closest to it in follower count (6,874 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 37% 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 0.001%, FlyOverChina sits below the 10th percentile of the 66,128 accounts in this comparison. That places it in the bottom 25% band, which runs below 0.016%.

p100.002%
p250.016%
p50 (median)0.1%
p750.499%
p902.09%
p99119.9%
Engagement rate as a share of followers, across the 66,128 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 57,111 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 percentile0.016%
50th percentile0.1%
75th percentile0.499%
90th percentile2.09%
99th percentile119.9%

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 08:00 UTC, and Wednesday 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: 08:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 111%Busiest hour: 08:00 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: Wednesday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 111%Busiest day: Wednesday
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 video100% of posts+111%+108% to +115%34K
Outbound link0% of posts-41%-42% to -40%32K
Typical length-no effect-2% to -1%42K
  • 100% 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 270 characters, which falls in the 180 - 280 characters band. Across the catalog, posts of 180 to 280 characters match the same accounts' other posts almost exactly.

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

  • Aug 16, 20264.3x their median

    A high-speed train races through the mist beside Pingtian Lake in Chizhou, east China's Anhui Province. Misty mountains, calm waters and a train in motion: a breathtaking meeting of modern speed and picturesque scenery. šŸš„ #flyoverchina #chinatravel #highspeedtrain https://t.co/weAJ9hkn7m

    525001.5K viewsView on X
  • Aug 26, 20262.6x their median

    Waves of ripening rice are rolling across the hills of Sanshan Village in Jingde County of Xuancheng, east China's Anhui Province. 🌾 What's the most beautiful harvest view you've ever seen? Drop it below! šŸ’¬ #HarvestSeason #RiceTerraces #Anhui #FlyOverChina #RuralChina https://t.co/pkmyzhtRqB

    11700883 viewsView on X
  • Jun 25, 20262.6x their median

    The Huangguoshu Waterfall in Anshun City, southwest China's Guizhou Province, has seen a significant surge in water flow due to continuous rainfall and increased upstream inflow in recent days. #AmazingChina #FlyOverChina #ChinaTravel #ChinaVibe #Waterfall https://t.co/1lhjV2nbGz

    512011.1K viewsView on X
  • Jul 11, 20262.3x their median

    🌪 Typhoon #Bavi, the ninth of 2026, is barreling toward eastern China with gales and heavy rain. China's national observatory has issued an orange alert, and regions like Jiangsu Province are already taking response measures to keep everyone safe. #FlyOverChina https://t.co/1zwMlLm3am

    412001.4K viewsView on X
  • Jun 13, 20261.9x their median

    It's harvest season in Qingdao and the wheat fields are buzzing with action! 🌾 Farmers are making the most of sunny weather with combine harvesters working at full speed. šŸ“ Shandong, east China #wheatharvest #qingdao #summervibes https://t.co/A54aTZi1Xg

    211001.0K viewsView on X
  • Aug 12, 2026

    Four types of fishing boats with special permission set sail on Tuesday after a three-month summer fishing ban in the East China Sea. The opening of the fishing season was delayed from the originally scheduled Aug. 5 due to Typhoon Dolphin. #Fishing #Sea #Fishingseason https://t.co/ysFNaxwbeG

    010001.3K viewsView on X
  • Jul 18, 2026

    Look up! šŸŒ™ The moon and Venus just had a stunning cosmic meetup over northeast China's Heilongjiang Province. Have you ever spotted a celestial pairing like this? Share your own sky-gazing moments in the comments! ⬇ #Moon #Venus #Heilongjiang #FlyOverChina https://t.co/045vccBzvI

    27101.3K viewsView on X
  • Jul 15, 2026

    China's foreign trade in yuan-denominated terms grew 16.9 percent year on year in the first half of 2026, data from the General Administration of Customs (GAC) showed Tuesday. #ChinaPulse #Chinamaxxing #trade https://t.co/JDZS684Xfj

    010001.1K viewsView on X
  • Jul 10, 2026

    In midsummer, creative rice paddy artworks decorated the vast fields of northeast China's Heilongjiang Province, a major grain-producing area in China. https://t.co/Qp45dMprQK

    64001.6K viewsView on X
  • Jun 7, 2026

    What a beautiful natural scenery. ✨ šŸŒ„ A breathtaking sea of clouds after the rain! šŸ“ Tashan Yao Township, Changning City, central China's Hunan Province #flyoverchina #ChinaTravel #ChinaVibe https://t.co/9jcpEmjedZ

    28001.1K 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.

Recurring topics

#chinatravel#flyoverchina#gansu#anhui#bridge

The most frequent hashtags in the sampled posts. They describe what this account writes about; they are not a performance signal, and the catalog-wide breakdown on the hub shows how little hashtag count moves.

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Reading these numbers

A typical post picks up 7 interactions against 644K followers, an engagement rate of 0.001%. Measured over 11 original posts, its engagement rate beats 10% of 6,874 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 1.1K times each, and 0.614% of those impressions turn into an interaction. That is about 0.177% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.37 posts a day over the last 30 days, though only 30% of days saw any activity at all. Most posts go out around 08:00 UTC, and Wednesday is the busiest day of the week. Of the 11 posts sampled, 100% carry an image or video. The account's strongest tracked post pulled 30 interactions, about 4.3x its own typical post. Recurring topics include #chinatravel, #flyoverchina, #gansu.

What is FlyOverChina's engagement rate on X?
FlyOverChina (@FlyOverChina) has an engagement rate of 0.001%, based on the median interactions across 11 original posts from the last 30 days against 644,094 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.001%, FlyOverChina sits below the 10th percentile of the 66,128 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 @FlyOverChina have real engagement?
Its engagement rate beats 10% of the tracked X accounts closest to it in follower count (6,874 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 @FlyOverChina post?
Most posts go out around 08:00 UTC, and Wednesday is its busiest day, at roughly 0.37 posts per day across the measured window.

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