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宝玉 engagement report

@dotey - 248K followers on X

Measured over 22 original posts from a 30-day window, last computed on September 9, 2026.

Engagement

Top quarter for its size
Per follower
0.273%
of 248K followers
Per impression
0.483%
139K views on a typical post
Reach
56.5%
of its followers see a post
Typical post
672
interactions (median)
Saved
0.141%
196 bookmarks on a typical post
Posting rate
2.77/day
active 30% of days
Peak time
03:00 UTC
Wednesday

A typical post picks up 672 interactions against 248K followers, an engagement rate of 0.273%. Measured over 22 original posts, its engagement rate beats 79% of 6,874 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 139K times each, and 0.483% of those impressions turn into an interaction. That is about 56.3% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 2.8 posts a day over the last 30 days, though only 30% of days saw any activity at all. Most posts go out around 03:00 UTC, and Wednesday is the busiest day of the week. Of the 22 posts sampled, 64% carry an image or video and 23% link out. The account's strongest tracked post pulled 14K interactions, about 21x its own typical post. Recurring topics include #astra, #blender, #gpt.

Measured over 22 original posts from a 30-day window, last computed on September 9, 2026. Recurring tags: #astra, #blender, #gpt.

Compared with accounts its own size

宝玉's engagement rate beats 79% 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 29% 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 0.273%, 宝玉 sits above the 50th percentile of the 66,258 accounts in this comparison. That places it in the above the median band, which runs 0.1% to 0.499%.

p100.002%
p250.016%
p50 (median)0.1%
p750.499%
p902.09%
p99119.6%
Engagement rate as a share of followers, across the 66,258 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 56,968 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 percentile119.6%

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 03:00 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: 03:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 111%Busiest hour: 03:00 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: Wednesday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 111%Busiest day: Wednesday
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 video64% of posts+111%+108% to +115%34K
Outbound link23% of posts-41%-42% to -40%32K
Typical length-no effect-2% to -1%42K
  • 64% 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.
  • 23% 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 275 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

  • Sep 9, 202621x their median

    Big one today — Tailwind is joining Shopify 🛍️ https://t.co/YxnYEOsXKc

    12K8131.0K390594K viewsView on X
  • May 26, 202318x their median

    What if we set GPT-4 free in Minecraft? ⛏️ I’m excited to announce Voyager, the first lifelong learning agent that plays Minecraft purely in-context. Voyager continuously improves itself by writing, refining, committing, and retrieving *code* from a skill library. GPT-4 unlocks a new paradigm: “training” is code execution rather than gradient descent. “Trained model” is a codebase of skills that Voyager iteratively composes, rather than matrices of floats. We are pushing no-gradient architecture to its limit. Voyager rapidly becomes a seasoned explorer. In Minecraft, it obtains 3.3× more unique items, travels 2.3× longer distances, and unlocks key tech tree milestones up to 15.3× faster than prior methods. We open-source everything. Let generalist agents emerge in Minecraft! Welcome you all to try today: https://t.co/1d3YocozsI Paper: https://t.co/JcWEasgtyI Code: https://t.co/KsvVf7rcl0 Deep dive with me: 🧵

    8.9K1.9K3446153.9M viewsView on X
  • Sep 6, 202614x their median

    okay Astra time to rickroll https://t.co/KvZdFZNew4

    8.7K3942063287.3M viewsView on X
  • Sep 9, 202610x their median

    There was a bit of a kerfuffle this morning with some banked resets not fully applying when used in ChatGPT Work and Codex. Everyone who used one in the affected time window is getting another one and an email to apologize.

    5.4K1421.3K161296K viewsView on X
  • Sep 7, 20267.7x their median

    Super interesting detail from inside OpenAI: The company hired a bunch of ex-Meta people. Some of these people wanted to invest heavily into internal tooling teams (Meta did it, worked great) OpenAI leadership resisted, saying that in an AGI-first world, there will be no internal tooling teams. And they were right: now, with Codex, there's a massive internal tools explosion, without having any internal tooling teams!

    4.9K14415240841K viewsView on X
  • Jul 17, 20264.3x their median

    Heard that some frontier models are basically a 48-layer transformer looped twice (48L x 2). Now we are introducing DeepLoop: Depth Scaling for Looped Transformers (https://t.co/jtxllo9aFF), making the loop transformer stable and scalable! https://t.co/Js8Zy96MqY

    2.6K2563228654K viewsView on X
  • Sep 5, 20263.5x their median

    🧠💰GPT-6 Astra Money Tip: 'Medium Effort' 1% less intelligence for 25% cost savings https://t.co/2cf0vmmxXn

    2.2K585323268K viewsView on X
  • Dec 3, 20252.6x their median

    A thread for my nana banana pro prompts 🧵 https://t.co/riAcKUtR6T

    1.4K14913732903K viewsView on X
  • Sep 9, 20261.8x their median

    We are investigating an issue that may be causing unexpected usage resets for some users. https://t.co/z7m3wg1uPS

    9073520172153K viewsView on X
  • Sep 1, 20261.8x their median

    https://t.co/UMTjznAJSc

    9481912729245K 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

#astra#blender#gpt

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 672 interactions against 248K followers, an engagement rate of 0.273%. Measured over 22 original posts, its engagement rate beats 79% of 6,874 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 139K times each, and 0.483% of those impressions turn into an interaction. That is about 56.3% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 2.8 posts a day over the last 30 days, though only 30% of days saw any activity at all. Most posts go out around 03:00 UTC, and Wednesday is the busiest day of the week. Of the 22 posts sampled, 64% carry an image or video and 23% link out. The account's strongest tracked post pulled 14K interactions, about 21x its own typical post. Recurring topics include #astra, #blender, #gpt.

What is 宝玉's engagement rate on X?
宝玉 (@dotey) has an engagement rate of 0.273%, based on the median interactions across 22 original posts from the last 30 days against 247,517 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.273%, 宝玉 sits above the 50th percentile of the 66,258 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 @dotey have real engagement?
Its engagement rate beats 79% of the tracked X accounts closest to it in follower count (6,874 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 @dotey post?
Most posts go out around 03:00 UTC, and Wednesday is its busiest day, at roughly 2.77 posts per day across the measured window.

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