Oracle Developers engagement report
@OracleDevs - 117K followers on X
Measured over 38 original posts from a 30-day window, last computed on October 7, 2026.
Engagement
A typical post picks up 24 interactions against 117K followers, an engagement rate of 0.021%. Measured over 38 original posts, its engagement rate beats 27% of 15,519 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 2.0K times each, and 1.20% of those impressions turn into an interaction. That is about 1.74% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.3 post a day over the last 30 days, with activity on roughly 73% of days. Most posts go out around 14:00 UTC, and Tuesday is the busiest day of the week. Of the 38 posts sampled, 89% carry an image or video and 89% link out. The account's strongest tracked post pulled 259 interactions, about 11x its own typical post. Recurring topics include #aiworld, #java27, #orclapex.
Measured over 38 original posts from a 30-day window, last computed on October 7, 2026. Recurring tags: #aiworld, #java27, #orclapex.
Compared with accounts its own size
Oracle Developers's engagement rate beats 27% of the tracked X accounts closest to it in follower count (15,519 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 45% 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 0.021%, Oracle Developers sits above the 10th percentile of the 156,839 accounts in this comparison. That places it in the bottom 25% band, which runs below 0.022%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.003% |
| 25th percentile | 0.022% |
| 50th percentile | 0.128% |
| 75th percentile | 0.604% |
| 90th percentile | 2.32% |
| 99th percentile | 83.4% |
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 14:00 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.
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 | 89% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 89% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | +15% | +14% to +16% | 32K |
- 89% 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.
- 89% of its posts carry a link off X. Across the catalog, posts with an outbound link run 41% below the same accounts' other posts, so a large share of this account's output sits in the weakest bucket we measure.
- Its average post runs 318 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 15, 202611x their median
#Java27 has arrived! 🥳☕ Get all the details about the latest release from our Java team. https://t.co/u2bfScIyn1 https://t.co/rt0A4gc5oa
- Oct 3, 20262.5x their median
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- Sep 20, 20262.1x their median
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- Sep 19, 20261.9x their median
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- Sep 16, 20261.6x their median
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- Sep 24, 20261.6x their median
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- Sep 29, 2026
As AI agents evolve beyond chat, developers need secure ways to connect models, enterprise data, and dynamic user interfaces. We demonstrate how to build A2UI and MCP Apps using Oracle AI Database and the Java MCP Toolkit, with examples that run in ChatGPT, Claude, and Google Gemini Enterprise. You'll learn: 👉 How to expose governed database capabilities through the Java MCP Toolkit instead of unrestricted database access 👉 When to use A2UI for host-native, declarative interfaces versus MCP Apps for portable, sandboxed web experiences 👉 How Oracle AI Database remains the authoritative layer for validation, transactions, and auditing while AI agents provide rich user experiences 👉 End-to-end architecture, deployment guidance, and complete reference code to accelerate your own agentic AI applications Check out this comprehensive walkthrough to get practical examples of MCP, A2UI, Oracle AI Database, agentic AI architecture, and enterprise AI application development: https://t.co/o5joDXCjEC
- Sep 18, 2026
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- Oct 2, 2026
By combining Oracle Kubernetes Engine, kagent, OCI Generative AI, and OCI DevOps, organizations can build a more intelligent and governed operations model. The result isn't just faster diagnosis, but better decision-making. Incidents are evaluated with context, remediations are controlled, and business-critical applications can be protected with greater confidence. This blog breaks it down: https://t.co/YJeUVfFcqH
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 24 interactions against 117K followers, an engagement rate of 0.021%. Measured over 38 original posts, its engagement rate beats 27% of 15,519 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 2.0K times each, and 1.20% of those impressions turn into an interaction. That is about 1.74% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.3 post a day over the last 30 days, with activity on roughly 73% of days. Most posts go out around 14:00 UTC, and Tuesday is the busiest day of the week. Of the 38 posts sampled, 89% carry an image or video and 89% link out. The account's strongest tracked post pulled 259 interactions, about 11x its own typical post. Recurring topics include #aiworld, #java27, #orclapex.
- What is Oracle Developers's engagement rate on X?
- Oracle Developers (@OracleDevs) has an engagement rate of 0.021%, based on the median interactions across 38 original posts from the last 30 days against 117,054 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.021%, Oracle Developers sits above the 10th percentile of the 156,839 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 @OracleDevs have real engagement?
- Its engagement rate beats 27% of the tracked X accounts closest to it in follower count (15,519 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 @OracleDevs post?
- Most posts go out around 14:00 UTC, and Tuesday is its busiest day, at roughly 1.33 posts per day across the measured window.