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Ainun Najib engagement report

@ainunnajib - 157K followers on X

Measured over 20 original posts from a 30-day window, last computed on September 22, 2026.

Engagement

Middle of its size range
Per follower
0.193%
of 157K followers
Per impression
0.671%
46K views on a typical post
Reach
28.7%
of its followers see a post
Typical post
306
interactions (median)
Saved
0.135%
62 bookmarks on a typical post
Posting rate
2.53/day
active 40% of days
Peak time
00:00 UTC
Monday

A typical post picks up 306 interactions against 157K followers, an engagement rate of 0.193%. Measured over 20 original posts, its engagement rate beats 66% of 20,444 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 46K times each, and 0.671% of those impressions turn into an interaction. That is about 28.9% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 2.5 posts a day over the last 30 days, though only 40% of days saw any activity at all. Most posts go out around 00:00 UTC, and Monday is the busiest day of the week. Of the 20 posts sampled, 65% carry an image or video, 10% are part of a thread and 20% link out. The account's strongest tracked post pulled 27K interactions, about 89x its own typical post.

Measured over 20 original posts from a 30-day window, last computed on September 22, 2026. Recurring tag: #bebaskangusyaqut.

Compared with accounts its own size

Ainun Najib's engagement rate beats 66% of the tracked X accounts closest to it in follower count (20,444 accounts, accounts of similar size (decile 8 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 31% 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 0.193%, Ainun Najib sits above the 50th percentile of the 205,261 accounts in this comparison. That places it in the above the median band, which runs 0.143% to 0.678%.

p100.004%
p250.024%
p50 (median)0.143%
p750.678%
p902.55%
p9982.4%
Engagement rate as a share of followers, across the 205,261 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 22,894 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 percentile0.004%
25th percentile0.024%
50th percentile0.143%
75th percentile0.678%
90th percentile2.55%
99th percentile82.4%

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 00:00 UTC, and Monday 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: 00:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 111%Busiest hour: 00:00 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: Monday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 111%Busiest day: Monday
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 video65% of posts+111%+108% to +115%34K
Outbound link20% of posts-41%-42% to -40%32K
Typical length-+15%+14% to +16%32K
  • 65% 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.
  • 20% 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 295 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

  • Sep 20, 202689x their median

    金型業界の衰退について書いたら、まったく違う業界の方から返信が来ました。 一つ読むごとに、手が止まりました。 「アパレルの国内生産比率は、もう1.1%です」 「美容業界では、ドライヤーもアイロンもクリッパーも、すでに修理不可能になっています」 「造船は日本にやられて、世界中の造船所が軍艦専門になった。今度は日本が苦境です」 「街の盤屋です。規格がJEM・JECからIECに変えられて、対応が難しくなっています」 「メーカーのサプライヤーですが、この数年でネジ屋、Oリング屋、ベルト屋、刃物屋、研ぎ屋、メッキ屋、精密金型屋が本当に激減した。代わりは、若いエンジニアがPCで注文するカタログ通販です」 同じことが、同じ順番で起きています。 最初に、安いほうへ移ります。 経営判断としては正しい。誰も間違っていません。 次に、国内の作り手が減ります。 ここでもまだ、誰も困りません。物は届くからです。 その次に、直せなくなります。 壊れたら買い替える。修理という選択肢が消える。 最後に、良し悪しがわかる人がいなくなります。 これが一番怖い。 うちの業界は、もうその手前まで来ています。 数字にも出ています。 2025年、日本の金型の輸出はおよそ2,000億円。 輸入はおよそ1,300億円。 そのうち中国からが約770億円です。 5年前と比べると、 中国への輸出は、およそ半分に減りました。 中国からの輸入は、およそ5割増えました。 金型は「物を作るための道具」です。 その道具を、日本は買う側に回りつつある。 何を、いくらで、いつ作れるか。 それを、よその国に決めてもらう側になるということです。 返信でいただいた言葉を、そのまま引きます。 「発注する側に、良し悪しのわかる人間がいなくなる。すでに分からないまま、前と一緒という理由で仕様を出す大手がいます」 「製造業と名ばかりの丸投げ代理店ばかりになり、公差もハメアイも粗さ記号も、鋼材の熱処理も分からない自称エンジニアが増えた」 検収できない人が発注し、検収できない人が受け取る。 そうなると、品質は誰にも見えなくなります。 悪くなったことにすら、気づけない。 そして、ある方がこう書いていました。 「同じことが、AIをめぐる近未来にも起きる。企画も経営も、果ては政治の提案までAIに委ねたとき、検収のできない我々はめくら判を押し続ける機械になる」 金型の話をしているつもりでした。 どうやら、そうではなかったようです。 自分の業界で、最後に「これは違う」と言える人は、あと何人残っていますか。 #金型 #製造業 #町工場の本音

    18K8.8K183540794K viewsView on X
  • Sep 20, 202650x their median

    https://t.co/sHwWIpclmo

    14K1.4K8951606K viewsView on X
  • Sep 14, 202622x their median

    Oxford researchers argue that LLMs can never invent anything. It is mathematically impossible. They published a paper called “Theory Is All You Need" and it argues against the claim that computational models can generate genuine novelty or new knowledge. They analyzed the limits of generative ai, and the results are a brutal reality check for the idea that ai will replace human decision making under uncertainty. Here is why AI is stuck and human cognition wins: backward-looking vs forward-looking.. llms are probability machines that look backward at existing data. human cognition is forward-looking and capable of generating genuine novelty. human cognition operates theoretically "top-down" rather than "bottom-up" from data. the "data-belief asymmetry".. the researchers use the invention of "heavier-than-air flight" to illustrate this concept. an ai relies on data-based prediction, which is largely imitative. humans, however, use theory-based causal logic that allows them to hold beliefs that go beyond existing data. the intervention gap.. humans don't just process information; we use theory to practically "intervene" in the world. we engage in directed experimentation to generate entirely new data. ai-based models are theory-free and place primacy on existing data and prediction. tldr? AI uses a probability-based approach to knowledge and ia largely imitative. It can process data and make predictions, but human cognition relies on theory-based causal reasoning. The decades-old analogy comparing human minds and computers to mere "input-output" devices is fundamentally flawed.

    5.0K1.1K424233359K viewsView on X
  • Nov 25, 202522x their median

    My take on the jagged frontier debate: https://t.co/7TaKLbEZeM

    5.7K4592503044.2M viewsView on X
  • Sep 17, 202619x their median

    Setiap Tersangkut Kasus Korupsi Di Rumahnya Mengadakan Doa bersama? Agama Di Jadikan Alat Untuk Membenarkan Perbuatan Korup? https://t.co/MdBphCDq6f

    3.7K1.6K575106190K viewsView on X
  • Sep 13, 202617x their median

    An important project I think everyone should do: I got a 16TB hard drive and I'm downloading as many open source models as I can This is insurance for the future. In case they are banned If you have them already downloaded, they can't be taken away from you And even if they aren't banned, it will be incredible to look back in 30 years and load up Qwen 3 just to see what life was like back then If you have a smaller hard drive, I still think this is worth doing to stay independent and free, and having intelligence whenever need it. Download any models you can get your hands on from HuggingFace It's preserving history and preserving your sovereignty

    4.4K36350279287K viewsView on X
  • Sep 14, 202613x their median

    🔴 BREAKING: Saudi Arabia has discovered 110 million tons of raw materials containing uranium concentrations in Medina, Saudi Energy Minister Prince Abdulaziz bin Salman says. https://t.co/MVDRQV3LS4

    2.9K6131221631.0M viewsView on X
  • Sep 20, 20269.2x their median

    Your job may be surviving on inertia. Your resentment won’t extend the runway. What do you actually want to do with the intelligence now at your disposal? https://t.co/vikawjCmZD

    2.3K291132114608K viewsView on X
  • Sep 14, 20268.0x their median

    We are the first generation with the tools to end scarcity.

    2.1K2041492148K viewsView on X
  • Sep 19, 20262.1x their median

    Beautiful. 10/10. No notes. https://t.co/EjhmfcJbWT

    51575271843K 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.

Recurring topics

#bebaskangusyaqut

The most frequent hashtags in the sampled posts. They describe what this account writes about; they are not a performance signal, and the catalog-wide breakdown on the hub shows how little hashtag count moves.

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Reading these numbers

A typical post picks up 306 interactions against 157K followers, an engagement rate of 0.193%. Measured over 20 original posts, its engagement rate beats 66% of 20,444 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 46K times each, and 0.671% of those impressions turn into an interaction. That is about 28.9% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 2.5 posts a day over the last 30 days, though only 40% of days saw any activity at all. Most posts go out around 00:00 UTC, and Monday is the busiest day of the week. Of the 20 posts sampled, 65% carry an image or video, 10% are part of a thread and 20% link out. The account's strongest tracked post pulled 27K interactions, about 89x its own typical post.

What is Ainun Najib's engagement rate on X?
Ainun Najib (@ainunnajib) has an engagement rate of 0.193%, based on the median interactions across 20 original posts from the last 30 days against 157,348 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.193%, Ainun Najib sits above the 50th percentile of the 205,261 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 @ainunnajib have real engagement?
Its engagement rate beats 66% of the tracked X accounts closest to it in follower count (20,444 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 @ainunnajib post?
Most posts go out around 00:00 UTC, and Monday is its busiest day, at roughly 2.53 posts per day across the measured window.

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