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ₕₐₘₚₜₒₙ engagement report

@hamptonism - 226K followers on X

Measured over 46 original posts from a 30-day window, last computed on October 1, 2026.

Engagement

Middle of its size range
Per follower
0.033%
of 226K followers
Per impression
1.09%
6.9K views on a typical post
Reach
3.07%
of its followers see a post
Typical post
76
interactions (median)
Saved
0.094%
6 bookmarks on a typical post
Posting rate
4.2/day
active 27% of days
Peak time
13:00 UTC
Friday

A typical post picks up 76 interactions against 226K followers, an engagement rate of 0.033%. Measured over 46 original posts, its engagement rate beats 40% of 20,944 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 6.9K times each, and 1.09% of those impressions turn into an interaction. That is about 3.08% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 4.2 posts a day over the last 30 days, though only 27% of days saw any activity at all. Most posts go out around 13:00 UTC, and Friday is the busiest day of the week. Of the 46 posts sampled, 54% carry an image or video and 7% link out. The account's strongest tracked post pulled 48K interactions, about 636x its own typical post.

Measured over 46 original posts from a 30-day window, last computed on October 1, 2026.

Compared with accounts its own size

ₕₐₘₚₜₒₙ's engagement rate beats 40% of the tracked X accounts closest to it in follower count (20,944 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 45% 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 0.033%, ₕₐₘₚₜₒₙ sits above the 25th percentile of the 211,975 accounts in this comparison. That places it in the below the median band, which runs 0.025% to 0.146%.

p100.004%
p250.025%
p50 (median)0.146%
p750.694%
p902.61%
p9983.1%
Engagement rate as a share of followers, across the 211,975 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 22,461 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 percentile0.025%
50th percentile0.146%
75th percentile0.694%
90th percentile2.61%
99th percentile83.1%

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 13:00 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.

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: 13:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 111%Busiest hour: 13:00 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: Friday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 111%Busiest day: Friday
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 video54% of posts+111%+108% to +115%34K
Outbound link7% of posts-41%-42% to -40%32K
Typical length-no effect-2% to -1%42K
  • 54% 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.
  • 7% 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 190 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

  • Sep 11, 2026636x their median

    iPhone Duo、まさかの外側ディスプレイがマグネット仕様! あとこのケースめちゃくちゃいいぞ… https://t.co/rg7E85PKWt

    43K2.8K7781.4K18M viewsView on X
  • Sep 9, 2026147x their median

    If you’re wondering what $20M looks like btw: https://t.co/Y7gCcZySms

    10K6902041864.6M viewsView on X
  • Sep 11, 2026126x their median

    Pokémon Center Tokyo (2008) https://t.co/aLIBkWp1Vr

    8.5K94610136282K viewsView on X
  • Sep 8, 202684x their median

    You can literally see the moment her brain begins to shut down from the fact Nathan knows something she doesn’t. https://t.co/U40OmFODNq

    6.0K1171021926.5M viewsView on X
  • Sep 29, 202644x their median

    for ten years every single peter thiel controversy has just been peter saying something actually interesting, propelled into virality by a mob of his most ardent haters who are either 1) responding to it out of context, or 2) genuinely too stupid to understand his point

    3.1K119861695K viewsView on X
  • Sep 10, 202622x their median

    Immediately after the Jacob/Anthropic tweet thread went viral, when it was at around 2m impressions, I screen recorded the first subtweeters as the diffusion/ propagation of the visit was obviously sync’d. I was certain, and said so at the time that the tweets were very highly suspect and bs. To do some light forensics, these days, as X cut off a lot of the tools/API I knew I had to catch the data in real time. I have , thru a shop I’m an investor in, the full x firehose, but whatever. Anyhoo, with this stuff it’s called ‘Graph Neural Networks’ = GNN It’s a graph of nodes that operate on graphs where nodes are connected by edges. A. Node (or a vertice) is a a network of users, the subtweeters B. edges are the relationships/interactions between them This is ‘neighborhood aggregation’ What you’re looking for, in the way I simplistically did it sans tools, is to look thru thr assorted influencers and subtweeters and see if their engagement is abnormal / too high And then also look for those accounts use of bots and inauthentic behavior Anyhoo

    1.4K2427046195K viewsView on X
  • Oct 1, 20269.5x their median

    🇯🇵 Tokyo has recorded rain for 36 consecutive days, the longest streak since records began in 1876. Aug 27: 🌧️ Aug 28: 🌧️ Aug 29: 🌧️ Aug 30: 🌧️ Aug 31: 🌧️ Sep 1: 🌧️ Sep 2: 🌧️ Sep 3: 🌧️ Sep 4: 🌧️ Sep 5: 🌧️ Sep 6: 🌧️ Sep 7: 🌧️ Sep 8: 🌧️ Sep 9: 🌧️ Sep 10: 🌧️ Sep 11: 🌧️ Sep 12: 🌧️ Sep 13: 🌧️ Sep 14: 🌧️ Sep 15: 🌧️ Sep 16: 🌧️ Sep 17: 🌧️ Sep 18: 🌧️ Sep 19: 🌧️ Sep 20: 🌧️ Sep 21: 🌧️ Sep 22: 🌧️ Sep 23: 🌧️ Sep 24: 🌧️ Sep 25: 🌧️ Sep 26: 🌧️ Sep 27: 🌧️ Sep 28: 🌧️ Sep 29: 🌧️ Sep 30: 🌧️ Oct 1: 🌧️

    62852271655K viewsView on X
  • Sep 10, 20264.9x their median

    https://t.co/K0arUFIa7W

    31138915422K viewsView on X
  • Sep 30, 20264.0x their median

    i’m at a point in my life where i find this sexy. https://t.co/XyZipZE65I

    28997138K viewsView on X
  • Sep 30, 20264.0x their median

    yea something is just not adding up… https://t.co/nIEvV8hmYL

    2801112343K 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 76 interactions against 226K followers, an engagement rate of 0.033%. Measured over 46 original posts, its engagement rate beats 40% of 20,944 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 6.9K times each, and 1.09% of those impressions turn into an interaction. That is about 3.08% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 4.2 posts a day over the last 30 days, though only 27% of days saw any activity at all. Most posts go out around 13:00 UTC, and Friday is the busiest day of the week. Of the 46 posts sampled, 54% carry an image or video and 7% link out. The account's strongest tracked post pulled 48K interactions, about 636x its own typical post.

What is ₕₐₘₚₜₒₙ's engagement rate on X?
ₕₐₘₚₜₒₙ (@hamptonism) has an engagement rate of 0.033%, based on the median interactions across 46 original posts from the last 30 days against 225,668 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.033%, ₕₐₘₚₜₒₙ sits above the 25th percentile of the 211,975 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 @hamptonism have real engagement?
Its engagement rate beats 40% of the tracked X accounts closest to it in follower count (20,944 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 @hamptonism post?
Most posts go out around 13:00 UTC, and Friday is its busiest day, at roughly 4.2 posts per day across the measured window.

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