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Port3 Network engagement report

@Port3Network - 289K followers on X

Measured over 3 original posts from a 30-day window, last computed on September 6, 2026.

Engagement

Per follower
0.002%
of 289K followers
Per impression
0.12%
4.2K views on a typical post
Reach
1.43%
of its followers see a post
Typical post
5
interactions (median)
Saved
0.024%
1 bookmarks on a typical post
Posting rate
0.13/day
active 13% of days
Peak time
08:00 UTC
Tuesday

Early reading. We have captured 3 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 5 interactions against 289K followers, an engagement rate of 0.002%. Posts are seen about 4.2K times each, and 0.12% of those impressions turn into an interaction. That is about 1.44% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.13 posts a day over the last 30 days, though only 13% of days saw any activity at all. Most posts go out around 08:00 UTC, and Tuesday is the busiest day of the week. Of the 3 posts sampled, 67% carry an image or video. The account's strongest tracked post pulled 2.9K interactions, about 580x its own typical post. Only 3 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 3 original posts from a 30-day window, last computed on September 6, 2026.

Where this sits in the catalog

At 0.002%, Port3 Network sits below the 10th percentile of the 66,393 accounts in this comparison. That places it in the bottom 25% band, which runs below 0.016%.

p100.002%
p250.016%
p50 (median)0.1%
p750.499%
p902.09%
p99119.5%
Engagement rate as a share of followers, across the 66,393 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 56,924 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 percentile0.016%
50th percentile0.1%
75th percentile0.499%
90th percentile2.09%
99th percentile119.5%

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 08:00 UTC, and Tuesday 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: 08:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 111%Busiest hour: 08:00 UTC
Show engagement by hour posted, utc as a table
Engagement by hour posted, UTC
Hour (UTC)Vs author medianPosts
00:00 UTC-1%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 UTC0%116K
22:00 UTC-2%100K
23:00 UTC-1%90K
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: Tuesday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 111%Busiest day: Tuesday
Show engagement by day of week as a table
Engagement by day of week
DayVs author medianPosts
Sunday+5%393K
Monday+1%483K
Tuesday-2%520K
Wednesday-3%472K
Thursday-2%430K
Friday-3%447K
Saturday+2%393K
See what moves engagement across the whole catalogWhat counts as a good engagement rate at this size

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.

This account's posting mix compared with catalog-wide effects
FormatThis accountCatalog effect95% intervalAccounts behind it
Image or video67% of posts+111%+108% to +115%34K
Outbound link0% of posts-41%-42% to -40%32K
Typical length--3%-3% to -2%54K
  • 67% 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 98 characters, which falls in the 80 - 180 characters band. Across the catalog, posts of 80 to 180 characters run 3% below 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

  • Aug 4, 2026580x their median

    JUST IN: Microsoft, Meta, Oracle, Amazon, & Alphabet have now locked in $1,090,000,000,000.00 in future AI data center lease payments.

    2.4K21019077601K viewsView on X
  • Apr 7, 2026490x their median

    The office is going extinct. Replaced by AI. For the first time ever, more offices were demolished than built. Meanwhile, AI data center construction just passed office construction -- also for the first time. https://t.co/GYgJykGqBq

    1.9K4408031188K viewsView on X
  • Apr 27, 2026186x their median

    The big dilemma with teaching an "LLM course" is that it is really easy to get drawn into teaching the various technical things like efficiency tricks, attention variants, PPO vs GRPO, etc etc. But the real "meat" is not there, but in the data: data for pre-training, for mid-training, for SFT, for RL and for "reasoning", synthetic data, curated data, annotated data... cleaning, evaluating, improving, mixing, ... lots of stuff. but "data" is so much harder to teach: it is not "mathematic" or "algorithmic" like the technical things, and it is not clear what is the teachable thing there. it is also a lot less transparent than the technical topics, both because it is semi-secret, and also because it is also not appealing for publishing, for roughly the same reasons it is not appealing for teaching. so, what would you teach about data? what are the key lessons and insights one should know? any good papers or resources? good existing classes? blogs? hit me with what you have

    8175554560K viewsView on X
  • Jun 1, 202691x their median

    Introducing Kled-FD 0.1, the world's best fraud detection and dataset cleaning pipeline. The first all in one system capable of detecting AI generated content, near duplicates, stolen and plagiarized media, screenshots, manipulated and spliced content, NSFW and explicit material, minors and age sensitive content, sensitive and harmful content, and coordinated behavioral fraud rings. Kled-FD 0.1 has been battle tested across 1.2 billion uploads on Kled's data marketplace and is actively running quality checks on over 5 million uploads per day across image, video, audio, and text. Public benchmarks will be released soon. This is the first real step toward making data quality enforcement a humanless process.

    3633154964K viewsView on X
  • Jun 28, 202623x their median

    NVIDIA just open sourced Nemotron 3 Ultra. > 550B parameters (55B active/token) > 1M token context > 47.7 on the AI Intelligence Index > 300+ tokens/sec > Open weights, datasets & training recipes Open source AI just got a serious upgrade. https://t.co/UPJuesABCF

    1003938.8K viewsView on X
  • Jun 28, 202616x their median

    As data volumes and complexity grow, data engineers need scalable ways to build, manage, and optimize pipelines. 📕 The Big Book of Data Engineering covers proven patterns for scaling ETL, orchestrating data and AI workloads, implementing observability, and managing pipelines with Lakeflow. You'll also see how organizations across Healthcare, Financial Services, Retail, and Entertainment are building intelligent batch and streaming data pipelines. https://t.co/Nvxjsl0MqQ

    738019.0K viewsView on X
  • May 19, 20267.2x their median

    Blackstone & Google launch $5B TPU cloud venture to bring 500MW of AI data center capacity online by 2027. "This joint venture ...helps meet growing demand for TPUs" - Google Cloud CEO: $CRWV: -5% PM $BX: +1% PM $GOOGL: +1% PM https://t.co/EG13R3MY3U

    253627.0K viewsView on X
  • Mar 29, 20263.4x their median

    Weekend plans: • Try new AI tools • Test agent workflows • Explore onchain activity • Read signal threads • Break a few things Build where data becomes intelligence.

    122211.5K viewsView on X
  • Mar 20, 20263.4x their median

    The AI training dataset market is exploding. From $3.19B in 2025 → $3.87B in 2026, growing at 21.5% CAGR. Behind every breakthrough model is a massive pipeline of labeled, structured data. The real #AI race isn’t just about models. It’s about who owns the data supply chain. https://t.co/a7vcTLEDhT

    101511.3K viewsView on X
  • Aug 12, 20263.0x their median

    GM. Time to stop scrolling noise. Start feeding the Agents that actually move. https://t.co/PMkWkDIlgz

    91504.2K 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 5 interactions against 289K followers, an engagement rate of 0.002%. Posts are seen about 4.2K times each, and 0.12% of those impressions turn into an interaction. That is about 1.44% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.13 posts a day over the last 30 days, though only 13% of days saw any activity at all. Most posts go out around 08:00 UTC, and Tuesday is the busiest day of the week. Of the 3 posts sampled, 67% carry an image or video. The account's strongest tracked post pulled 2.9K interactions, about 580x its own typical post. Only 3 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 Port3 Network's engagement rate on X?
Port3 Network (@Port3Network) has an engagement rate of 0.002%, based on the median interactions across 3 original posts from the last 30 days against 289,385 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.002%, Port3 Network sits below the 10th percentile of the 66,393 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 @Port3Network have real engagement?
There is not yet enough sample to rank this account against others of its size.
When does @Port3Network post?
Most posts go out around 08:00 UTC, and Tuesday is its busiest day, at roughly 0.13 posts per day across the measured window.

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