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Polyhedra engagement report

@PolyhedraZK - 867K followers on X

Measured over 2 original posts from a 30-day window, last computed on August 29, 2026.

Engagement

Per follower
0.004%
of 867K followers
Per impression
0.329%
11K views on a typical post
Reach
1.31%
of its followers see a post
Typical post
38
interactions (median)
Saved
0.004%
0 bookmarks on a typical post
Posting rate
0.2/day
active 7% of days
Peak time
19:00 UTC
Wednesday

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 38 interactions against 867K followers, an engagement rate of 0.004%. Posts are seen about 11K times each, and 0.329% of those impressions turn into an interaction. That is about 1.31% 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 7% of days saw any activity at all. Most posts go out around 19:00 UTC, and Wednesday is the busiest day of the week. Of the 2 posts sampled, 100% carry an image or video. The account's strongest tracked post pulled 675 interactions, about 18x 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 August 29, 2026.

Where this sits in the catalog

At 0.004%, Polyhedra sits above the 10th percentile of the 37,701 accounts in this comparison. That places it in the bottom 25% band, which runs below 0.012%.

p100.002%
p250.012%
p50 (median)0.081%
p750.439%
p902.10%
p99156.3%
Engagement rate as a share of followers, across the 37,701 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 104,204 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 percentile0.081%
75th percentile0.439%
90th percentile2.10%
99th percentile156.3%

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 19:00 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.

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: 19:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 6%Busiest hour: 19:00 UTC
Show engagement by hour posted, utc as a table
Engagement by hour posted, UTC
Hour (UTC)Vs author medianPosts
00:00 UTC-1%53K
01:00 UTC-2%53K
02:00 UTC-3%52K
03:00 UTC-4%55K
04:00 UTC-6%44K
05:00 UTC-4%43K
06:00 UTC-4%50K
07:00 UTC-5%54K
08:00 UTC-4%63K
09:00 UTC-3%72K
10:00 UTC-2%75K
11:00 UTC-3%81K
12:00 UTC-2%90K
13:00 UTC-2%98K
14:00 UTC-3%101K
15:00 UTC-2%105K
16:00 UTC-4%102K
17:00 UTC-3%95K
18:00 UTC-1%88K
19:00 UTC-2%83K
20:00 UTC-1%77K
21:00 UTC-1%69K
22:00 UTC-2%60K
23:00 UTC-2%53K
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: Wednesday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 5%Busiest day: Wednesday
Show engagement by day of week as a table
Engagement by day of week
DayVs author medianPosts
Sunday+5%238K
Monday0%302K
Tuesday-3%302K
Wednesday-1%257K
Thursday-2%250K
Friday-3%259K
Saturday+3%233K
See what moves engagement across the whole catalogWhat counts as a good engagement rate at this size

Best tweets

  • Jan 2, 202618x their median

    2025 was a year we had to fight for. From zkML progress on major models, advancing ExpChain toward mainnet, and launching Ocash mainnet alpha, redefining how privacy, compliance, and AI payments can coexist. We never stopped building. 2026 will be bigger. Read full blog here. https://t.co/Vzx6QOq5LY

    296294751086K viewsView on X
  • May 21, 20261.8x their median

    ๐—›๐—ฎ๐˜€๐—ต ๐—œ๐˜ ๐—ข๐˜‚๐˜ โ€” ๐—š๐—ผ๐—ผ๐—ฑ ๐—”๐—ด๐—ฒ๐—ป๐˜๐˜€ ๐——๐—ผ๐—ปโ€™๐˜ ๐—›๐—ฎ๐—น๐—น๐˜‚๐—ฐ๐—ถ๐—ป๐—ฎ๐˜๐—ฒ How long will we keep dealing with hallucinations? TCโ€™s take: With good agents, the problem is already becoming manageable. โ†’ Careful prompting matters โ†’ Every claim can be fact-checked โ†’ References can be enforced โ†’ Agents can verify their own outputs The future of AI reliability wonโ€™t come from bigger models alone. Itโ€™ll come from better systems around them. ๐Ÿ‘‡ Taken from Hash It Out with @Tiancheng_Xie & @Tony0kai https://t.co/jUMwYUGqud

    3243313.9K viewsView on X
  • Apr 17, 20261.6x their median

    Google disclosed a quantum vulnerability using a zero-knowledge proof. The technology they used to responsibly warn the world about the collapse of classical cryptography โ€” is the same class of proof system our team has spent a decade building. Our co-founder and CTO @Tiancheng_Xie sat down with @Tony0kai on the first episode of Hash It Out to unpack what this means - for AI, for post-quantum security, and for the role zero-knowledge infrastructure plays in both. They covered: โ†’ Google's breakthrough and why they disclosed it via ZK โ†’ AI collapsing the economics of cybersecurity - $1.4B drained from crypto in the past year โ†’ Why verifiable computation matters more as AI models become more capable โ†’ The real timeline for post-quantum migration Zero-knowledge proofs were designed to prove truth without revealing secrets.

    3991215.1K viewsView on X
  • Apr 30, 20261.6x their median

    ๐—›๐—ฎ๐˜€๐—ต ๐—œ๐˜ ๐—ข๐˜‚๐˜ โ€” ๐—”๐˜๐˜๐—ฎ๐—ฐ๐—ธ ๐—ฎ๐—ป๐—ฑ ๐——๐—ฒ๐—ณ๐—ฒ๐—ป๐˜€๐—ฒ ๐—”๐—ฟ๐—ฒ ๐˜๐—ต๐—ฒ ๐—ฆ๐—ฎ๐—บ๐—ฒ ๐—š๐—ฎ๐—บ๐—ฒ AI is making cyberattacks faster. But hereโ€™s what most people miss: โ†’ Attack and defense run the same process โ†’ Both are about finding bugs โ†’ The only difference is: exploit vs fix TCโ€™s take: Once a bug is found, fixing it is easy. Finding it is the hard part. Thatโ€™s why defense can keep up. ๐Ÿ‘‡ Taken from Hash It Out with @Tiancheng_Xie & @Tony0kai https://t.co/ivtopaFB8h

    2862426.9K viewsView on X
  • Apr 28, 2026

    AI can now execute full-scale cyberattacks. But thatโ€™s not the real problem. The real problem is: you no longer know what to trust. Our co-founder and CTO @Tiancheng_Xie sat down with @Tony0kai on the latest episode of Hash It Out to break down whatโ€™s actually changing โ€” across AI security, multi-agent systems, and post-quantum infrastructure. They covered: โ†’ Why Claude Mythos completing a 32-step network attack changes the economics of cybersecurity โ†’ How AI makes attacks cheaper โ€” but also makes defense scale the same way โ†’ Why closed-source advantages in cyber models may only last 6โ€“12 months โ†’ The real risk in multi-agent systems: prompt injection, fake data, and loss of control โ†’ Why zero-knowledge proofs donโ€™t stop attacks โ€” but make systems verifiable โ†’ How post-quantum security is becoming a race to define the next internet standard As AI systems become more autonomous, the challenge isnโ€™t just preventing attacks: Itโ€™s proving that what youโ€™re running โ€” your model, your data, your agents โ€” is actually what you think it is. Thatโ€™s the layer most systems still donโ€™t have, and exactly what weโ€™re building. ๐ŸŽฅ Watch the full episode: https://t.co/gjwyDlR7UB

    3221817.8K viewsView on X
  • Aug 12, 2026

    1/ An account is supposed to represent one person. But in practice, thatโ€™s no longer always true. Across platforms, a single identity is often used by multiple people โ€” sometimes intentionally, sometimes not. Hereโ€™s whatโ€™s happening ๐Ÿ‘‡ https://t.co/1ujCOxOdar

    24717111K viewsView on X
  • May 27, 2026

    1/ Passwords are disappearing. Across major platforms, authentication is shifting toward devices โ€” passkeys, biometrics, and hardware-backed credentials. Your phone or laptop is becoming your identity. But that shift comes with a new assumption. Hereโ€™s whatโ€™s happening ๐Ÿ‘‡ https://t.co/TqMrL8Kb4N

    326915.6K viewsView on X
  • May 15, 2026

    ๐— ๐—ผ๐˜€๐˜ ๐—ฝ๐—ฒ๐—ผ๐—ฝ๐—น๐—ฒ ๐—ฎ๐˜€๐˜€๐˜‚๐—บ๐—ฒ ๐˜๐—ต๐—ฒ ๐—ฏ๐—ฒ๐˜€๐˜ ๐—”๐—œ ๐—บ๐—ผ๐—ฑ๐—ฒ๐—น ๐—ด๐—ถ๐˜ƒ๐—ฒ๐˜€ ๐˜๐—ต๐—ฒ ๐—ฏ๐—ฒ๐˜€๐˜ ๐—ฎ๐—ป๐˜€๐˜„๐—ฒ๐—ฟ๐˜€. Not necessarily. TC explains why: โ†’ Models are still months behind real-world events โ†’ They donโ€™t automatically know todayโ€™s news โ†’ Without the right workflow, hallucinations happen A powerful model is only part of the system. ๐Ÿ‘‡ Taken from Hash It Out with @Tiancheng_Xie & @Tony0kAI https://t.co/jUMwYUGqud

    356313.3K viewsView on X
  • Apr 29, 2026

    1/ Healthcare is no longer confined to hospitals and clinics. Telemedicine platforms now allow doctors and patients to connect through video calls, online consultations, and digital health services. Medical care is increasingly happening through screens. Hereโ€™s whatโ€™s changing ๐Ÿ‘‡ https://t.co/qsEK8zcyt8

    319324.3K viewsView on X
  • Apr 22, 2026

    1/ Online marketplaces have made it possible for anyone to become a seller. In minutes, a new storefront can appear, listing products and accepting payments from customers around the world. But as e-commerce scales, a critical question is becoming harder to answer: Who is actually behind the seller account? Hereโ€™s whatโ€™s happening ๐Ÿ‘‡

    2751016.3K 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 38 interactions against 867K followers, an engagement rate of 0.004%. Posts are seen about 11K times each, and 0.329% of those impressions turn into an interaction. That is about 1.31% 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 7% of days saw any activity at all. Most posts go out around 19:00 UTC, and Wednesday is the busiest day of the week. Of the 2 posts sampled, 100% carry an image or video. The account's strongest tracked post pulled 675 interactions, about 18x 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 Polyhedra's engagement rate on X?
Polyhedra (@PolyhedraZK) has an engagement rate of 0.004%, based on the median interactions across 2 original posts from the last 30 days against 867,144 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.004%, Polyhedra sits above the 10th percentile of the 37,701 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 @PolyhedraZK have real engagement?
There is not yet enough sample to rank this account against others of its size.
When does @PolyhedraZK post?
Most posts go out around 19:00 UTC, and Wednesday is its busiest day, at roughly 0.2 posts per day across the measured window.

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