Freakonomics engagement report
@Freakonomics - 580K followers on X
Measured over 8 original posts from a 30-day window, last computed on October 10, 2026.
Engagement
A typical post picks up 16 interactions against 580K followers, an engagement rate of 0.003%. Measured over 8 original posts, its engagement rate beats 20% of 19,932 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 10K times each, and 0.153% of those impressions turn into an interaction. That is about 1.80% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.6 post a day over the last 30 days, though only 33% of days saw any activity at all. Most posts go out around 13:00 UTC, and Saturday is the busiest day of the week. Of the 8 posts sampled, 100% carry an image or video, 63% are part of a thread and 25% link out. The account's strongest tracked post pulled 83 interactions, about 5.2x its own typical post.
Measured over 8 original posts from a 30-day window, last computed on October 10, 2026.
Compared with accounts its own size
Freakonomics's engagement rate beats 20% of the tracked X accounts closest to it in follower count (19,932 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 11% 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 0.003%, Freakonomics sits below the 10th percentile of the 201,555 accounts in this comparison. That places it in the bottom 25% band, which runs below 0.024%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.004% |
| 25th percentile | 0.024% |
| 50th percentile | 0.142% |
| 75th percentile | 0.671% |
| 90th percentile | 2.53% |
| 99th percentile | 82.5% |
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 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.
Show engagement by hour posted, utc as a table
| Hour (UTC) | Vs author median | Posts |
|---|---|---|
| 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 UTC | 0% | 116K |
| 22:00 UTC | -2% | 100K |
| 23:00 UTC | -1% | 90K |
Show engagement by day of week as a table
| Day | Vs author median | Posts |
|---|---|---|
| Sunday | +5% | 393K |
| Monday | +1% | 483K |
| Tuesday | -2% | 520K |
| Wednesday | -3% | 472K |
| Thursday | -2% | 430K |
| Friday | -3% | 447K |
| Saturday | +2% | 393K |
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.
| Format | This account | Catalog effect | 95% interval | Accounts behind it |
|---|---|---|---|---|
| Image or video | 100% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 25% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | +15% | +14% to +16% | 32K |
- 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.
- 25% 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 372 characters, which falls in the over 280 characters band. Across the catalog, posts over 280 characters run 15% above 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 8, 20265.2x their median
We’ll take “Things That Made Our Day” for $2,000. https://t.co/Nb1cDEUN3F
- Sep 17, 20264.2x their median
Kurt Warner doesn’t believe great athletes rise to the occasion. The Hall of Fame quarterback has played in some of football’s biggest arenas. But when Stephen Dubner asked what made him so good under pressure, Warner offered a different way of thinking about it … Maybe the greats don’t suddenly get better when the stakes are highest. Maybe most people shrink under pressure. This week on Freakonomics Radio, @kurt13warner talks about why it’s so hard to predict which quarterbacks will succeed in the NFL.
- Aug 9, 20262.8x their median
Social clubs. Churches. Synagogues. Bowling leagues. Maybe they mattered more than we realized. Rabbi Angela Buchdahl and Stephen Dubner on YouTube now. https://t.co/e8z935oR57 https://t.co/pObwP4HzvF
- Aug 9, 20262.0x their median
If you're going to make something new, take some risks and try to make it NEW. Stephen explains the thinking behind Better in Person. Watch it now on the Freakonomics YouTube channel. https://t.co/5iTUdOMZbi https://t.co/Ycuf06MO2w
- Aug 10, 20261.8x their median
$750 billion. That's roughly how much is being spent on A.I. infrastructure today. Current revenues from A.I. are only a fraction of that. As former S.E.C. chair Gary Gensler says, we’ve seen that kind of imbalance before. This week on Freakonomics Radio, Stephen Dubner talks with Gensler about the economics behind the A.I. boom, why investment often races ahead of revenue, and what history can teach us about what happens next.
- Sep 26, 20261.5x their median
When is a bet not a bet? Our two-part series on prediction markets has generated a lot of discussion from our listeners. Many of you are dead-set against the very idea of them. Freakonomics Radio producer Theo Jacobs has spent the past few months digging into some of the thornier questions that prediction markets haven’t yet answered.
- Oct 1, 2026
Good game, better conversation. Thank you, Ed! https://t.co/Wh4AaeZnzC
- Sep 1, 2026
This week on Better in Person... 30 years ago, James Daunt was an independent bookseller. Today, he’s C.E.O. of Barnes & Noble (@BNBuzz) and running the very bookstore chains that once ruled the industry. His philosophy on running a global chain? Think local. https://t.co/6fUS4a1pFB
- Aug 22, 2026
She's won a Pulitzer and still sometimes feels like an imposter. @Egangoonsquad https://t.co/SRHuMXJoVU
- Aug 16, 2026
Warren Zanes prices in the value of mistakes. https://t.co/tJgZnFIHsU
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.
Buy or sell Twitter (X) accounts - escrow-protected
PlayerSells is an escrow marketplace for Twitter (X) accounts. Every deal is protected, with no middleman risk.
Reading these numbers
A typical post picks up 16 interactions against 580K followers, an engagement rate of 0.003%. Measured over 8 original posts, its engagement rate beats 20% of 19,932 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 10K times each, and 0.153% of those impressions turn into an interaction. That is about 1.80% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.6 post a day over the last 30 days, though only 33% of days saw any activity at all. Most posts go out around 13:00 UTC, and Saturday is the busiest day of the week. Of the 8 posts sampled, 100% carry an image or video, 63% are part of a thread and 25% link out. The account's strongest tracked post pulled 83 interactions, about 5.2x its own typical post.
- What is Freakonomics's engagement rate on X?
- Freakonomics (@Freakonomics) has an engagement rate of 0.003%, based on the median interactions across 8 original posts from the last 30 days against 580,450 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.003%, Freakonomics sits below the 10th percentile of the 201,555 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 @Freakonomics have real engagement?
- Its engagement rate beats 20% of the tracked X accounts closest to it in follower count (19,932 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 @Freakonomics post?
- Most posts go out around 13:00 UTC, and Saturday is its busiest day, at roughly 0.6 posts per day across the measured window.