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Sabine Hossenfelder engagement report

@skdh - 237K followers on X

Measured over 23 original posts from a 30-day window, last computed on September 30, 2026.

Engagement

Top quarter for its size
Per follower
0.35%
of 237K followers
Per impression
2.24%
37K views on a typical post
Reach
15.6%
of its followers see a post
Typical post
820
interactions (median)
Saved
0.221%
81 bookmarks on a typical post
Posting rate
4/day
active 73% of days
Peak time
15:00 UTC
Tuesday

A typical post picks up 820 interactions against 237K followers, an engagement rate of 0.35%. Measured over 23 original posts, its engagement rate beats 80% of 20,444 tracked accounts of a similar size. Comparing inside a size band matters here: engagement rate falls as accounts grow, so a raw rate would mostly just re-measure the follower count. Posts are seen about 37K times each, and 2.24% of those impressions turn into an interaction. That is about 15.5% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 4 posts a day over the last 30 days, with activity on roughly 73% of days. Most posts go out around 15:00 UTC, and Tuesday is the busiest day of the week. Of the 23 posts sampled, 39% carry an image or video and 65% link out. The account's strongest tracked post pulled 4.3K interactions, about 5.2x its own typical post.

Measured over 23 original posts from a 30-day window, last computed on September 30, 2026.

Compared with accounts its own size

Sabine Hossenfelder's engagement rate beats 80% 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 66% 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 0.35%, Sabine Hossenfelder sits above the 50th percentile of the 205,048 accounts in this comparison. That places it in the above the median band, which runs 0.143% to 0.678%.

p100.004%
p250.024%
p50 (median)0.143%
p750.678%
p902.55%
p9982.4%
Engagement rate as a share of followers, across the 205,048 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 22,894 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 percentile0.678%
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 15:00 UTC, and Tuesday 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: 15:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 111%Busiest hour: 15:00 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: Tuesday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 111%Busiest day: Tuesday
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 video39% of posts+111%+108% to +115%34K
Outbound link65% of posts-41%-42% to -40%32K
Typical length-no effect-2% to -1%42K
  • 39% 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.
  • 65% of its posts carry a link off X. Across the catalog, posts with an outbound link run 41% below the same accounts' other posts, so a large share of this account's output sits in the weakest bucket we measure.
  • Its average post runs 271 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 21, 20265.2x their median

    Nuclear fusion just got a reality check. Researchers from MIT checked which fusion designs have a chance of ever making economic sense. They carefully evaluated the construction and maintenance costs and the expected profit made by selling energy. Their calculations suggest that the relevant metric is the amount of power produced per surface area surrounding the plasma. If correct, this strongly disfavors large machines like ITER, whereas compact high-field tokamak designs such as SPARC and modern stellarator designs have a fair chance of breaking financially even. The researchers find that the best strategy is not to make the reactor exceptionally durable but rather to make sure that radiation-damaged parts can be replaced quickly and at a low cost. Technologies that use inertial confinement via lasers or ion beams also meet the target, but they have a secondary problem: they must produce large numbers of targets cheaply. Paper here https://t.co/G0rbiBsw9f Press release here https://t.co/ylaOsUYn64

    3.6K37426155520K viewsView on X
  • Sep 9, 20264.0x their median

    Physicists should put together a list of mathematically well-defined problems that could advance the field. Such as, eg, what constitutes a low-temperature superconductor, what are the lattice conditions for cold fusion (or why do they not exist), what is a local completion of quantum mechanics, what is the simplest (in terms of computational complexity) way to obtain the masses and coupling constants of the standard model, what is the UV-completion of MOND or why isn't there any, is there any provably UV-finite version of quantum gravity, etc etc

    2.9K2231803391K viewsView on X
  • Sep 21, 20264.0x their median

    Degrowthers are dangerous https://t.co/eI7s24ooLa

    2.5K423221103149K viewsView on X
  • Sep 20, 20263.3x their median

    US Government Misstated COVID Vaccine Risk The British Medical Journal (BMJ) reports that during the COVID vaccine rollout in 2021, US health officials used a safety-monitoring algorithm that they knew was inadequate but ignored the problem. At the time, the Food and Drug Administration (FDA) compared reports of adverse events after each vaccine with reports after other vaccines. But by 2021 more than 90 per cent of reports were about the (very similar) mRNA vaccines from Pfizer and Moderna. Because of this, adverse events which occured for both vaccines would not have statistically stood out. The BMJ extracted this information from internal emails it obtained under the Freedom of Information Act. These emails reveal that FDA employees Ana Szarfman and statistician William DuMouchel warned Peter Marks (then the FDA’s vaccine regulator) about this problem in early 2021. They proposed an improved method, but higher FDA administration ignored the warning. As a consequence, the algorithm failed to flag myocarditis (an inflammation of the heart muscle), which was later found to be a side-effect of mRNA vaccination. Report here: https://t.co/YwogjHVi2R

    2.0K36021259113K viewsView on X
  • Sep 9, 20263.2x their median

    Btw the Navier Stokes problem comes down to: if we lived in a truly continuous universe, fluids might sometimes explode. It’s an issue for the universe of classical mathematics, but does not apply to the computational universe we are in.

    2.4K9413419357K viewsView on X
  • Sep 26, 20263.0x their median

    Neuroscience has a big problem with reproducibility and it only seems to be getting worse https://t.co/mZLyxFU0d3

    2.0K30613567186K viewsView on X
  • Sep 8, 20262.6x their median

    well, I guess I have to look for a different hobby now: https://t.co/F8vvHkAoP5

    1.8K81190754K viewsView on X
  • Sep 5, 20262.4x their median

    If you trust the headlines, then every country on the planet is warming faster than the rest, which can't possibly be true, can it? I've had a look at the headline-making papers. https://t.co/byZ4MIRkEm

    1.6K227952647K viewsView on X
  • Sep 18, 2026

    idk I think my left ear has moved https://t.co/nvavnbIqrK

    1.0K18172425K viewsView on X
  • Sep 21, 2026

    when a "breakthrough" AI paper gets published and it's about GPT 3.5 https://t.co/s7w2papDwq

    1.1K2951332K 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 820 interactions against 237K followers, an engagement rate of 0.35%. Measured over 23 original posts, its engagement rate beats 80% of 20,444 tracked accounts of a similar size. Comparing inside a size band matters here: engagement rate falls as accounts grow, so a raw rate would mostly just re-measure the follower count. Posts are seen about 37K times each, and 2.24% of those impressions turn into an interaction. That is about 15.5% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 4 posts a day over the last 30 days, with activity on roughly 73% of days. Most posts go out around 15:00 UTC, and Tuesday is the busiest day of the week. Of the 23 posts sampled, 39% carry an image or video and 65% link out. The account's strongest tracked post pulled 4.3K interactions, about 5.2x its own typical post.

What is Sabine Hossenfelder's engagement rate on X?
Sabine Hossenfelder (@skdh) has an engagement rate of 0.35%, based on the median interactions across 23 original posts from the last 30 days against 236,646 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.35%, Sabine Hossenfelder sits above the 50th 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 @skdh have real engagement?
Its engagement rate beats 80% of the tracked X accounts closest to it in follower count (20,444 accounts), which puts it in the top 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 @skdh post?
Most posts go out around 15:00 UTC, and Tuesday is its busiest day, at roughly 4 posts per day across the measured window.

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