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Rowan Cheung engagement report

@rowancheung - 596K followers on X

Measured over 8 original posts from a 30-day window, last computed on August 26, 2026.

Engagement

Middle of its size range
Per follower
0.046%
of 596K followers
Per impression
0.601%
45K views on a typical post
Reach
7.61%
of its followers see a post
Typical post
273
interactions (median)
Saved
0.228%
104 bookmarks on a typical post
Posting rate
1.17/day
active 37% of days
Peak time
15:00 UTC
Monday

A typical post picks up 273 interactions against 596K followers, an engagement rate of 0.046%. Measured over 8 original posts, its engagement rate beats 57% of 3,774 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 45K times each, and 0.601% of those impressions turn into an interaction. That is about 7.61% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.2 post a day over the last 30 days, though only 37% of days saw any activity at all. Most posts go out around 15:00 UTC, and Monday is the busiest day of the week. Of the 8 posts sampled, 75% carry an image or video and 100% are part of a thread. The account's strongest tracked post pulled 1.7K interactions, about 6.3x its own typical post.

Measured over 8 original posts from a 30-day window, last computed on August 26, 2026.

Compared with accounts its own size

Rowan Cheung's engagement rate beats 57% of the tracked X accounts closest to it in follower count (3,774 accounts, accounts of similar size (decile 8 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 39% 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 0.046%, Rowan Cheung sits above the 25th percentile of the 36,521 accounts in this comparison. That places it in the below the median band, which runs 0.012% to 0.08%.

p100.002%
p250.012%
p50 (median)0.08%
p750.434%
p902.10%
p99160.7%
Engagement rate as a share of followers, across the 36,521 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 107,166 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 percentile0.012%
50th percentile0.08%
75th percentile0.434%
90th percentile2.10%
99th percentile160.7%

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 Monday 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 6%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%50K
01:00 UTC-2%51K
02:00 UTC-3%50K
03:00 UTC-4%53K
04:00 UTC-6%43K
05:00 UTC-4%42K
06:00 UTC-4%48K
07:00 UTC-5%52K
08:00 UTC-4%60K
09:00 UTC-3%69K
10:00 UTC-2%72K
11:00 UTC-3%78K
12:00 UTC-2%86K
13:00 UTC-2%94K
14:00 UTC-4%97K
15:00 UTC-2%100K
16:00 UTC-3%97K
17:00 UTC-2%90K
18:00 UTC-1%84K
19:00 UTC-2%79K
20:00 UTC-1%74K
21:00 UTC-1%66K
22:00 UTC-2%57K
23:00 UTC-2%51K
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: Monday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 5%Busiest day: Monday
Show engagement by day of week as a table
Engagement by day of week
DayVs author medianPosts
Sunday+4%230K
Monday0%286K
Tuesday-2%276K
Wednesday-1%251K
Thursday-1%244K
Friday-3%252K
Saturday+3%227K
See what moves engagement across the whole catalogWhat counts as a good engagement rate at this size

Best tweets

  • Apr 22, 20266.3x their median

    MIT researchers just replicated human muscles with AI-controlled fibers. Inside each fiber is a sealed tube of electrically charged liquid and a tiny electric pump. When the pump activates, one side contracts while the other relaxes, just as your biceps and triceps do when you bend your arm. How it works: > The pump injects electrical charge into the fluid > This creates ions that drag the liquid along with them > No motors, no external pumps, completely silent Because they're fibers, they bundle together just like real muscles, scaling up force by adding more strands. In demos, these fibers were strong enough to bend a robotic arm and curl a dumbbell... but gentle enough to shake someone's hand. From prosthetics to exoskeletons to industrial robots, this is what happens when engineers stop building around motors and start building around biology.

    1.3K2657648139K viewsView on X
  • May 4, 20265.5x their median

    Today we're announcing @_panthalassa’s $140M Series B, led by Peter Thiel, with participation from John Doerr and many other incredible investors. The mission: unlock the ocean as another planetary-scale energy resource for humanity. First stop: compute. https://t.co/uNO2hehyEf

    1.2K1426562319K viewsView on X
  • Jul 28, 20265.3x their median

    Mark Zuckerberg is running Meta's superintelligence lab like a startup. When I interviewed him, he told me the principles on how he built the team: "You don't need many hundreds of people. You need 50 to 100 people. It's a group science project who can keep the whole thing in their head at once. Seats on the boat are precious." "If someone is not pulling their weight on that, it has this huge negative effect in the way that it doesn't have on other parts of the company" "I wanna know who the top AI researchers are, and I wanna personally have relationships with them, and build the strongest team we can." His rules for running it: - If someone isn't pulling their weight, it has an outsized negative effect, so he personally went out and recruited every top researcher himself - No top-down deadlines. "It's research. You don't know how long the thing is gonna take." - Keep the org flat. No non-technical management layers, because once someone stops doing the work, "the knowledge decays."

    1.3K959115181K viewsView on X
  • May 26, 20263.6x their median

    Google DeepMind CEO Demis Hassabis says we’re in the ‘foothills of the singularity’ I sat down with him to talk about what that means, curing every disease, and human meaning post-AGI: 0:00 Intro 0:45 What Demis is most excited about at I/O 1:46 Have AGI timelines shifted? 3:30 What's still missing before AGI 6:50 AI curing every disease 9:19 What diseases get cured first? 10:50 What Demis works on after AGI 11:48 Human meaning after AGI 13:50 The human skills that get more valuable 15:19 What's underhyped in AI right now

    7481269229120K viewsView on X
  • Jun 29, 20263.1x their median

    There's a startup trying to build data centers in the ocean. And it's INCREDIBLY fascinating: Mass consumption of electricity and water is a growing bottleneck for data centers. So by moving offshore, it eliminates both problems -- the ocean provides unlimited cooling, and the waves provide unlimited power. There are also no engines, so the data centers drive themselves to their destination by using the shape of their hull to propel through waves. Called Panthalassa.

    6316612424148K viewsView on X
  • Oct 10, 20252.7x their median

    I'm HIRING 7 exceptional people and paying a $2,000 referral bonus for each We’ve bootstrapped The Rundown to $10M+ annual revenue and need to scale faster We’re tackling one of the biggest problems of the decade: helping 1B workers turn AI into a superpower Open roles: -Mobile Developer -GM, AI Univeristy -Head of Growth -Strategic Partnerships Lead -Product Marketing -Platform Designer -Thumbnail Designer We move faster than any company you've worked at. Competitive comp with performance-based scaling as we grow Every role requires deep taste and AI fluency. You'll be expected to command an army of AI agents working underneath you. Fully remote. Apply with the link below.

    586438812382K viewsView on X
  • Aug 10, 20262.2x their median

    A missile engineer got tired of mosquitoes... so he built an autonomous drone that hunts them Malaria kills over 600,000 people every year, most of them children under 5, so this could save millions of lives Here's how it works: > Each drone weighs 40 grams (lighter than a golf ball) > It fires ultrasonic pulses and listens through an array of tiny microphones, reading the Doppler signature of an insect's wings > That signal lets it tell a mosquito apart from a bee, then chase the target down and intercept it mid-air with propellers The company is backed by YC, and the founder previously engineered guidance and navigation systems for missiles. It's a legitimate project. They believe 10 drones could clear an entire square kilometre, cutting the cost of mosquito control by 100x So far though, the only public demo (below) was killing a moth in an enclosed room. Whether it works on a mosquito in the wild is the real test ahead

    47440601490K viewsView on X
  • Apr 13, 20262.0x their median

    Microsoft's AI can now detect cancer from a $10 tissue sample. For context, every time tumor cells are tested, doctors create a basic microscope slide to study tissue up close. These slides show cell shapes and structures, but they can't reveal which immune cells are actually fighting the cancer. That deeper picture is critical for knowing if a patient will respond to immunotherapy... But the advanced imaging needed costs THOUSANDS. So Microsoft built GigaTIME -- an AI system that generates advanced imaging from the cheap slides hospitals already collect. The system was trained on 40 million cancer cells, then applied to over 14,000 patients across 51 hospitals spanning 24 cancer types. The AI found over 1,200 hidden connections between immune cell behavior and tumor growth that researchers couldn't find before... because the data simply didn't exist at this scale. When validated against 10,000 additional patients from a completely separate database, the results held up. The model is now open source, so any hospital worldwide can use it on samples they already have. I think this is one of the most impactful AI papers I've seen this year!

    40998211544K viewsView on X
  • Aug 2, 20261.9x their median

    We just launched the Reddit for AI use cases. A place for builders to learn from other builders on how they're using AI to get ahead in life, work, and business. The submissions have been INCREDIBLE so far. A few of my favorites:

    419325416172K viewsView on X
  • May 4, 20261.8x their median

    Meta is planning to power its AI data centers with solar energy beamed from space. If it works, solar farms could produce power 24/7 without batteries or backup generators. The company behind it all is Overview Energy -- they want to launch 1,000 satellites into orbit, 22,000 miles above the equator, where sunlight is constant. For context, Meta's data centers used over 18,000 gigawatt-hours of electricity last year. Enough to power 1.7 million American homes for a year. Each satellite collects solar energy, converts it into a wide beam of near-infrared light, and aims it at existing solar farms on the ground. The farms convert the light into electricity, just like they do with sunlight. Unlike high-power lasers or microwave beams, this infrared light is safe enough to stare directly into. Solar farms normally sit idle at night, so this system fixes that... from space. Really fascinating tech.

    34043971270K 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 273 interactions against 596K followers, an engagement rate of 0.046%. Measured over 8 original posts, its engagement rate beats 57% of 3,774 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 45K times each, and 0.601% of those impressions turn into an interaction. That is about 7.61% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.2 post a day over the last 30 days, though only 37% of days saw any activity at all. Most posts go out around 15:00 UTC, and Monday is the busiest day of the week. Of the 8 posts sampled, 75% carry an image or video and 100% are part of a thread. The account's strongest tracked post pulled 1.7K interactions, about 6.3x its own typical post.

What is Rowan Cheung's engagement rate on X?
Rowan Cheung (@rowancheung) has an engagement rate of 0.046%, based on the median interactions across 8 original posts from the last 30 days against 596,491 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.046%, Rowan Cheung sits above the 25th percentile of the 36,521 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 @rowancheung have real engagement?
Its engagement rate beats 57% of the tracked X accounts closest to it in follower count (3,774 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 @rowancheung post?
Most posts go out around 15:00 UTC, and Monday is its busiest day, at roughly 1.17 posts per day across the measured window.

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