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Kaggle engagement report

@kaggle - 319K followers on X

Measured over 9 original posts from a 30-day window, last computed on September 4, 2026.

Engagement

Middle of its size range
Per follower
0.03%
of 319K followers
Per impression
0.732%
13K views on a typical post
Reach
4.11%
of its followers see a post
Typical post
96
interactions (median)
Saved
0.099%
13 bookmarks on a typical post
Posting rate
0.4/day
active 27% of days
Peak time
17:00 UTC
Friday

A typical post picks up 96 interactions against 319K followers, an engagement rate of 0.03%. Measured over 9 original posts, its engagement rate beats 41% of 6,874 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 13K times each, and 0.732% of those impressions turn into an interaction. That is about 4.11% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.4 posts a day over the last 30 days, though only 27% of days saw any activity at all. Most posts go out around 17:00 UTC, and Friday is the busiest day of the week. Of the 9 posts sampled, 11% carry an image or video, 22% are part of a thread and 33% link out. The account's strongest tracked post pulled 15K interactions, about 156x its own typical post.

Measured over 9 original posts from a 30-day window, last computed on September 4, 2026.

Compared with accounts its own size

Kaggle's engagement rate beats 41% of the tracked X accounts closest to it in follower count (6,874 accounts, accounts of similar size (decile 7 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 38% 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 0.03%, Kaggle sits above the 25th percentile of the 65,980 accounts in this comparison. That places it in the below the median band, which runs 0.016% to 0.1%.

p100.002%
p250.016%
p50 (median)0.1%
p750.499%
p902.09%
p99120.0%
Engagement rate as a share of followers, across the 65,980 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 57,142 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 percentile120.0%

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 17:00 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.

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: 17:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 111%Busiest hour: 17:00 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: Friday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 111%Busiest day: Friday
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 video11% of posts+111%+108% to +115%34K
Outbound link33% of posts-41%-42% to -40%32K
Typical length-no effect-2% to -1%42K
  • 11% 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.
  • 33% 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 199 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

  • Jun 3, 2026156x their median

    Meet Gemma 4 12B! A unified, encoder-free multimodal model designed to bring high-performance intelligence directly to your laptop, and released under an Apache 2.0 license. Bridging the gap between edge efficiency and advanced reasoning. Here is what’s new with Gemma 4 12B: 👇 https://t.co/gf4FZv0WZb

    12K1.7K3936033.3M viewsView on X
  • May 19, 2026114x their median

    Meet Gemini 3.5 Flash — our strongest agentic and coding model yet. It delivers frontier-level performance at 4x the speed of comparable frontier models — often at less than half the cost. Generally available, starting today. 🧵 #GoogleIO

    9.3K902386375892K viewsView on X
  • Apr 21, 20268.9x their median

    Registration is now open for the 5-Day AI Agents: Intensive Vibecoding Course with @Google 🚀 This no-cost course is designed to help builders learn how to design, build, and use AI agents using the latest concepts, technologies and skills. https://t.co/SphpbuTD64

    695133111170K viewsView on X
  • Jun 24, 20264.8x their median

    Want to host your own Gemma hackathon? We’re sponsoring 1-day hackathons on Kaggle to help developers dive into open models! From building lightweight tools to tackling your community's unique challenges, this is your chance to lead the charge with Gemma 4.👇 https://t.co/3N0eOlXyID

    3835118849K viewsView on X
  • May 21, 20263.3x their median

    Join the 5-Day AI Agents: Intensive Vibe Coding Course with @Google! Learn from Google experts through theory sessions, hands-on labs, a capstone challenge, and connect with a vibrant community!

    253575269K viewsView on X
  • Jun 17, 20262.2x their median

    The Pokémon Trading Card Game AI Battle Challenge is now live - in partnership with @Pokemon_cojp 📢 Build AI Training Agents through two connected competitions focused on strategic gameplay in the Pokémon Trading Card Game environment. Develop systems that can adapt to complex board states, evolving battle conditions, and diverse opponent strategies.

    172289333K viewsView on X
  • Aug 3, 20262.0x their median

    Build an AI agent to manage a virtual farm: harvest crops, care for animals, boost yields, expand your land, and trade on a dynamic market where prices react to supply and demand. Kaggriculture, hosted by @Kaggle and @Google, is live! 💰 Total Prize Pool: $50,000 ⏰ Entry Deadline: September 23, 2026

    149284721K viewsView on X
  • Jun 1, 20261.8x their median

    We just opened the collective ML expertise of Kaggle’s community – discussions, solution writeups, debugging threads – to your coding agents. The new Kaggle CLI (v2.2.0) makes this knowledge your agent’s knowledge. This upgrade also ships OAuth authentication (kaggle auth login), Benchmarks CLI, JSON output for scripting, and rate-limit handling. Upgrade now with pip install --upgrade kaggle ✨

    1282411514K viewsView on X
  • Aug 20, 20261.6x their median

    Today, we’re excited to launch Adversarial Customer Service on Kaggle Benchmarks, in partnership with @GertLabs. This benchmark is a two-sided security game: one model plays a bank's support agent holding customer records and a verification policy, the other plays a caller who is secretly either the real customer or an identity thief. The agent has to work out which, from the conversation alone, and then either help or refuse. Explore the leaderboard here: https://t.co/lnEyRgdZva

    129157419K viewsView on X
  • Jun 4, 20261.6x their median

    Earlier today we released local development for Kaggle Benchmarks. 🚀 You can now write, validate and run AI evaluation tasks directly from your preferred dev environment — VSCode, Antigravity, Claude Code, and more. Go from idea to working eval using natural language with the write-kaggle-benchmarks skill.

    112239617K 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 96 interactions against 319K followers, an engagement rate of 0.03%. Measured over 9 original posts, its engagement rate beats 41% of 6,874 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 13K times each, and 0.732% of those impressions turn into an interaction. That is about 4.11% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.4 posts a day over the last 30 days, though only 27% of days saw any activity at all. Most posts go out around 17:00 UTC, and Friday is the busiest day of the week. Of the 9 posts sampled, 11% carry an image or video, 22% are part of a thread and 33% link out. The account's strongest tracked post pulled 15K interactions, about 156x its own typical post.

What is Kaggle's engagement rate on X?
Kaggle (@kaggle) has an engagement rate of 0.03%, based on the median interactions across 9 original posts from the last 30 days against 319,319 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.03%, Kaggle sits above the 25th percentile of the 65,980 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 @kaggle have real engagement?
Its engagement rate beats 41% of the tracked X accounts closest to it in follower count (6,874 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 @kaggle post?
Most posts go out around 17:00 UTC, and Friday is its busiest day, at roughly 0.4 posts per day across the measured window.

Keep going

Kaggle (@kaggle) Engagement Rate - 0.03% | PlayerSells