Perceptron Network engagement report
@PerceptronNTWK - 244K followers on X
Measured over 13 original posts from a 30-day window, last computed on September 26, 2026.
Engagement
A typical post picks up 589 interactions against 244K followers, an engagement rate of 0.24%. Measured over 13 original posts, its engagement rate beats 77% of 15,519 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 15K times each, and 4.06% of those impressions turn into an interaction. That is about 5.93% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.47 posts a day over the last 30 days, with activity on roughly 47% of days. Most posts go out around 14:00 UTC, and Friday is the busiest day of the week. Of the 13 posts sampled, 100% carry an image or video. The account's strongest tracked post pulled 52K interactions, about 88x its own typical post.
Measured over 13 original posts from a 30-day window, last computed on September 26, 2026.
Compared with accounts its own size
Perceptron Network's engagement rate beats 77% of the tracked X accounts closest to it in follower count (15,519 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 84% 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 0.24%, Perceptron Network sits above the 50th percentile of the 157,102 accounts in this comparison. That places it in the above the median band, which runs 0.128% to 0.604%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.003% |
| 25th percentile | 0.022% |
| 50th percentile | 0.128% |
| 75th percentile | 0.604% |
| 90th percentile | 2.32% |
| 99th percentile | 83.4% |
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 14:00 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.
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 | - | no effect | -2% to -1% | 42K |
- 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 277 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
- May 6, 202688x their median
Not everyone gets access. 👀 If you’re part of one of these communities, you already know what this means. Submit your wallet in Discord to redeem your exclusive role + unlock what’s coming next. 🎯 Discord: https://t.co/hYRtRJeVjK 🔗 The gate is open… but not for everyone. 🟠 #PerceptronNTWK #NodeAndProud #AI #DecentralizedAI
- May 21, 202625x their median
Most data networks see the internet from a handful of servers. Perceptron sees it from 150+ countries - through real devices, run by real people. Human-in-the-loop signal intelligence. At global scale. #PerceptronNTWK #AI #DecentralizedAI #ATEOV https://t.co/bbXG75b4m6
- May 26, 202620x their median
"The AI stack is scaling fast. But the missing layer is still data acquisition. @sama has said that data is one of the major bottlenecks in AI development. AI needs fresh, real-world data that can't be pulled from static training sets. That's what Perceptron is building. https://t.co/oon9cbatNa
- May 28, 202619x their median
What 800K+ nodes means in practice: Perceptron doesn't depend on just one source. It has a distributed surface across 150+ countries. The ability to see the internet from every angle, all at once. No centralized team can replicate this capability. https://t.co/W5fUXyaYF7
- May 11, 202619x their median
We’re not waiting for big tech to own the data layer. We’re building it from the ground up - one node, one quest, one human at a time. https://t.co/aHRs46dCuv
- Jun 4, 202619x their median
Human-backed data is not about adding sentiment to AI. It's about turning human contributions into data AI can actually use. Intelligence can only go so far. Some things, only a human can catch. Perceptron is building the bridge. https://t.co/YfnxYT1b9A
- May 1, 20263.5x their median
▪️Add glue to pizza to help cheese stick better ▪️Eat 1 small rock per day to increase minerals in your body ▪️Mix bleach with vinegar for better cleaning results No, we are not crazy. These are just some examples of answers provided by AI chats. You see, quality and context REALLY do matter. And that’s something only humans can add. What’s the funniest wrong answer AI gave you yet? 💬
- Jun 9, 202618x their median
Many AI projects are still selling a concept. Perceptron is already running a live network: 800K+ total nodes. 100K daily active nodes. 150+ countries. 10 TB average daily bandwidth. This is what infrastructure in motion looks like at a global scale. https://t.co/eHR7UT28HV
- May 6, 202618x their median
Human-in-the-loop = Better AI Simple. Get in with Perceptron 👇 https://t.co/GDYYukTbd8
- May 5, 202618x their median
Synthetic data: friend or foe? It’s scaling AI fast…but at what cost to quality and real-world accuracy? Read the full breakdown on our latest article 👇 https://t.co/88xIBtO57E
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 589 interactions against 244K followers, an engagement rate of 0.24%. Measured over 13 original posts, its engagement rate beats 77% of 15,519 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 15K times each, and 4.06% of those impressions turn into an interaction. That is about 5.93% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.47 posts a day over the last 30 days, with activity on roughly 47% of days. Most posts go out around 14:00 UTC, and Friday is the busiest day of the week. Of the 13 posts sampled, 100% carry an image or video. The account's strongest tracked post pulled 52K interactions, about 88x its own typical post.
- What is Perceptron Network's engagement rate on X?
- Perceptron Network (@PerceptronNTWK) has an engagement rate of 0.24%, based on the median interactions across 13 original posts from the last 30 days against 244,441 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.24%, Perceptron Network sits above the 50th percentile of the 157,102 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 @PerceptronNTWK have real engagement?
- Its engagement rate beats 77% of the tracked X accounts closest to it in follower count (15,519 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 @PerceptronNTWK post?
- Most posts go out around 14:00 UTC, and Friday is its busiest day, at roughly 0.47 posts per day across the measured window.