宝玉 engagement report
@dotey - 263K followers on X
Measured over 42 original posts from a 30-day window, last computed on September 27, 2026.
Engagement
A typical post picks up 682 interactions against 263K followers, an engagement rate of 0.272%. Measured over 42 original posts, its engagement rate beats 76% of 21,185 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 127K times each, and 0.536% of those impressions turn into an interaction. That is about 48.4% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 5.3 posts a day over the last 30 days, with activity on roughly 57% of days. Most posts go out around 03:00 UTC, and Wednesday is the busiest day of the week. Of the 42 posts sampled, 64% carry an image or video, 10% are part of a thread and 29% link out. The account's strongest tracked post pulled 19K interactions, about 27x its own typical post. Recurring topics include #astra, #blender, #gpt.
Measured over 42 original posts from a 30-day window, last computed on September 27, 2026. Recurring tags: #astra, #blender, #gpt.
Compared with accounts its own size
宝玉's engagement rate beats 76% of the tracked X accounts closest to it in follower count (21,185 accounts, accounts of similar size (decile 9 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 28% 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 0.272%, 宝玉 sits above the 50th percentile of the 212,482 accounts in this comparison. That places it in the above the median band, which runs 0.146% to 0.696%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.004% |
| 25th percentile | 0.025% |
| 50th percentile | 0.146% |
| 75th percentile | 0.696% |
| 90th percentile | 2.61% |
| 99th percentile | 82.9% |
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.
Show engagement by hour posted, utc as a table
| Hour (UTC) | Vs author median | Posts |
|---|---|---|
| 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 UTC | 0% | 116K |
| 22:00 UTC | -2% | 100K |
| 23:00 UTC | -1% | 90K |
Show engagement by day of week as a table
| Day | Vs author median | Posts |
|---|---|---|
| Sunday | +5% | 393K |
| Monday | +1% | 483K |
| Tuesday | -2% | 520K |
| Wednesday | -3% | 472K |
| Thursday | -2% | 430K |
| Friday | -3% | 447K |
| Saturday | +2% | 393K |
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.
| Format | This account | Catalog effect | 95% interval | Accounts behind it |
|---|---|---|---|---|
| Image or video | 64% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 29% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | +15% | +14% to +16% | 32K |
- 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.
- 29% 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 329 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 9, 202627x their median
Big one today — Tailwind is joining Shopify 🛍️ https://t.co/YxnYEOsXKc
- Sep 9, 202619x 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.
- Sep 25, 202617x their median
Here’s to the wanting. Here’s to the dreaming. Here’s to everyone. https://t.co/FHcmqU3fYf
- 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: 🧵
- Sep 6, 202614x their median
okay Astra time to rickroll https://t.co/KvZdFZNew4
- Sep 25, 20269.3x their median
What is effort really? When do you change it it and why not just use max effort for everything? I dove deep into this problem, looking into evals and doing my own tests and I was quite surprised by the results. https://t.co/KO2D51j34H
- Sep 25, 20269.2x their median
Opus 5.5 is 20% cheaper per input and output token than Opus 5, and 60% cheaper on cache reads. So what does that actually do to the cost of a task in Claude Code? We ran the numbers, and built a calculator so you can run yours from /usage: https://t.co/WUqoFoecW3
- Sep 25, 20268.3x their median
🚨BREAKING: Claude is officially a NATIONAL SECURITY THREAT and is BLACKLISTED from the ENTIRE defense supply chain >anthropic: no autonomous weapons, no mass surveillance, no exceptions >pentagon blacklists claude as an active national security threat >anthropic sues Federal court ruled 2–1 AGAINST Anthropic: "As Anthropic admits, the company encodes restrictions into Claude that prevent the model from performing tasks that Anthropic wishes to prevent." "On more than one occasion, these restrictions have stopped Claude from performing tasks requested by government users": >refused to perform "tasks that were appropriate in a national security context" >refused CDC queries on infectious disease prevention research >anthropic questioned claude's use in the military operations "Anthropic's Chief Science Officer explained how the company 'seek[s] to embed safety considerations directly into the model itself.'" "[Anthropic's] CEO explained how such training gives the model an 'identity, character, values, and personality' of its own, tethered to a 'constitution' developed to impose 'high-level principles and values' on Claude itself." "We have no reason to doubt that Anthropic manipulates Claude's function with noble intentions... BUT the statutory definition of a 'supply chain risk' turns on what Anthropic does, not why Anthropic does it." "In our Republic, it is the President and the Secretary of War who must determine how best to balance the competing risks. In doing so here, the Secretary DID NOT transgress any limits on his authority." ITS OVER. ANTHROPIC IPO IN SHAMBLES
- Sep 7, 20267.6x 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!
- Sep 23, 20264.8x their median
Damn!! I feel like this is what the Vision Air was supposed to be. Zuck just introduced Meta VR glasses https://t.co/Ge5At3Y8o0
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
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 682 interactions against 263K followers, an engagement rate of 0.272%. Measured over 42 original posts, its engagement rate beats 76% of 21,185 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 127K times each, and 0.536% of those impressions turn into an interaction. That is about 48.4% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 5.3 posts a day over the last 30 days, with activity on roughly 57% of days. Most posts go out around 03:00 UTC, and Wednesday is the busiest day of the week. Of the 42 posts sampled, 64% carry an image or video, 10% are part of a thread and 29% link out. The account's strongest tracked post pulled 19K interactions, about 27x 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 0.272%, based on the median interactions across 42 original posts from the last 30 days against 262,715 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.272%, 宝玉 sits above the 50th percentile of the 212,482 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 76% of the tracked X accounts closest to it in follower count (21,185 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 5.3 posts per day across the measured window.