Rowan Cheung engagement report
@rowancheung - 602K followers on X
Measured over 2 original posts from a 30-day window, last computed on October 9, 2026.
Engagement
Early reading. We have captured 2 original posts for this account, below the 8 we require before treating a median as settled. The numbers above describe what we have seen so far, not a finished profile of the account.
A typical post picks up 200 interactions against 602K followers, an engagement rate of 0.033%. Posts are seen about 34K times each, and 0.598% of those impressions turn into an interaction. That is about 5.57% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.2 posts a day over the last 30 days, though only 10% of days saw any activity at all. Most posts go out around 15:00 UTC, and Wednesday is the busiest day of the week. Of the 2 posts sampled, 100% carry an image or video and 100% are part of a thread. The account's strongest tracked post pulled 58K interactions, about 290x its own typical post. Only 2 original posts have been captured so far, fewer than the 8 posts we want behind a median before treating it as settled. Read the figures above as an early measurement of this account, not as a finished profile of it.
Measured over 2 original posts from a 30-day window, last computed on October 9, 2026.
Where this sits in the catalog
At 0.033%, Rowan Cheung sits above the 25th percentile of the 204,313 accounts in this comparison. That places it in the below the median band, which runs 0.024% to 0.143%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.004% |
| 25th percentile | 0.024% |
| 50th percentile | 0.143% |
| 75th percentile | 0.677% |
| 90th percentile | 2.55% |
| 99th percentile | 82.4% |
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 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.
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 | 0% 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.
- 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 330 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
- Jul 9, 2026290x their median
(1) Today we're releasing Muse Spark 1.1 -- a strong agentic and coding model at a very low price. It's available through our new Meta Model API and in Meta AI.
- Apr 22, 20268.6x 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.
- May 4, 20267.5x 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
- Jul 28, 20267.2x 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."
- May 26, 20265.0x 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
- Jun 29, 20264.2x 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.
- Oct 10, 20253.6x 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.
- Aug 2, 20263.0x 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:
- Aug 10, 20262.9x 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
- Apr 13, 20262.3x 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!
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 200 interactions against 602K followers, an engagement rate of 0.033%. Posts are seen about 34K times each, and 0.598% of those impressions turn into an interaction. That is about 5.57% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.2 posts a day over the last 30 days, though only 10% of days saw any activity at all. Most posts go out around 15:00 UTC, and Wednesday is the busiest day of the week. Of the 2 posts sampled, 100% carry an image or video and 100% are part of a thread. The account's strongest tracked post pulled 58K interactions, about 290x its own typical post. Only 2 original posts have been captured so far, fewer than the 8 posts we want behind a median before treating it as settled. Read the figures above as an early measurement of this account, not as a finished profile of it.
- What is Rowan Cheung's engagement rate on X?
- Rowan Cheung (@rowancheung) has an engagement rate of 0.033%, based on the median interactions across 2 original posts from the last 30 days against 601,997 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.033%, Rowan Cheung sits above the 25th percentile of the 204,313 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?
- There is not yet enough sample to rank this account against others of its size.
- When does @rowancheung post?
- Most posts go out around 15:00 UTC, and Wednesday is its busiest day, at roughly 0.2 posts per day across the measured window.