Javarevisited engagement report
@javarevisited - 87K followers on X
Measured over 14 original posts from a 30-day window, last computed on September 28, 2026.
Engagement
A typical post picks up 10 interactions against 87K followers, an engagement rate of 0.011%. Measured over 14 original posts, its engagement rate beats 19% of 21,185 tracked accounts of a similar size. That is a reason to look at how the audience behaves - reply depth, saves, whether the followers are recent - rather than a conclusion about it on its own. Posts are seen about 2.8K times each, and 0.359% of those impressions turn into an interaction. That is about 3.20% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 2.7 posts a day over the last 30 days, with activity on roughly 47% of days. Most posts go out around 01:00 UTC, and Saturday is the busiest day of the week. Of the 14 posts sampled, 36% carry an image or video, 7% are part of a thread and 57% link out. The account's strongest tracked post pulled 7.9K interactions, about 785x its own typical post. Recurring topics include #courses, #onlineresources, #bestofjavarevisited.
Measured over 14 original posts from a 30-day window, last computed on September 28, 2026. Recurring tags: #courses, #onlineresources, #bestofjavarevisited.
Compared with accounts its own size
Javarevisited's engagement rate beats 19% of the tracked X accounts closest to it in follower count (21,185 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 18% 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 0.011%, Javarevisited sits above the 10th percentile of the 212,741 accounts in this comparison. That places it in the bottom 25% band, which runs below 0.025%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.004% |
| 25th percentile | 0.025% |
| 50th percentile | 0.146% |
| 75th percentile | 0.697% |
| 90th percentile | 2.61% |
| 99th percentile | 82.8% |
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 01:00 UTC, and Saturday 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 | 36% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 57% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | no effect | -2% to -1% | 42K |
- 36% 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.
- 57% 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 185 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
- Aug 28, 2026785x their median
Meet Javagal Srinath He is the only Indian fast bowler to capture over 300 wickets in One Day Internationals (finishing with 315 ODI wickets). Test Record: He was the second Indian pace bowler (after Kapil Dev) to reach 200 Test wickets, concluding his Test career with 236 wickets. World Cup Consistency: Represented India across four Cricket World Cups (1992, 1996, 1999, and 2003). He took 44 World Cup wickets, making him the joint-highest wicket-taker for India in World Cup history alongside Zaheer Khan.
- Sep 25, 20264.0x their median
I Tried 30+ System Design Courses: Here Are My Top 5 Recommendations for 2026 by @javinpaul https://t.co/6gdaeRNCX0 https://t.co/x2Ik7LrHmP
- Aug 21, 20264.0x their median
5 Books Every AI Developer Should Read in 2026 1. The LLM Engineering Handbook by @pauliusztin_ @maximelabonne - https://t.co/4ZKi54APbH 2. AI Engineering by @chipro - https://t.co/mccVtawXiQ 3. Designing Machine Learning Systems by @chipro - https://t.co/mXPxaB5Z9h 4. Building LLMs for Production by @Whats_AI @_LouiePeters - https://t.co/wy9BZIHDNR 5. Build a Large Language Model (from Scratch) by @rasbt - https://t.co/NTcR9KOZUZ
- Aug 28, 20261.9x their median
Employee: I'm pregnant. Due in March. Manager: Congratulations. Have you thought about your plan? Employee: I'll take my 12 weeks and be back in june. Manager: We just want to make sure the team is covered. Employee: I'll document everything before I leave. Manager: We've decided to restructure your role. Employee: I'm sorry? Manager: It's just business. She was restructured out three weeks before her due date. They called it a layoff. Gave her two weeks severance. Her position was reposted under a different title four months later. Her CEO just spoke at a Women in Leadership conference. The keynote was about "building inclusive workplaces." She watched it from her couch while nursing her daughter.
- Aug 26, 20261.9x their median
10 Must Read Data Structures and Algorithms Books for Developers 1. Introduction to Algorithms 4th Edition by Thomas H. Corman - https://t.co/V5HaxCk6Oh 2. Grokking Algorithms 2nd Edition by Aditya Bhargava - https://t.co/YGL9sJOYkn 3. Algorithms by Robert Sedgewick & Kevin Wayne - https://t.co/1DdHLV3OwE 4. The Algorithm Design Manual 3rd Edition by Steve S. Skiena - https://t.co/9brFzNdifP
- Aug 26, 20261.7x their median
10 Timeless Books Every Java Developers Should Read 1. Head First Java - https://t.co/gLoJvJe34k 2. Effective Java - https://t.co/KgZuwlnrZY 3. Head First Design Patterns - https://t.co/eoBPETvkjX 4. Java Concurrency in Practice - https://t.co/QgrGRBDG6J 5. Java By Comparison - https://t.co/kwP4GdDXYA 6. Clean Code : https://t.co/oG3fnGGUdz 7. The Pragmatic Programme: https://t.co/MGMUYGPGtK 8. Refactoring, Improving design of existing code https://t.co/I6XzLUPQ8n 9. Working Effectively with Legacy Code - https://t.co/4YA5QfYNNt 10. Code Complete https://t.co/MLnY52D4oc
- Sep 19, 20261.5x their median
Senior Engineer with 18 years of system design experience. Interview: “Implement LRU cache from scratch.”
- Sep 24, 2026
How OAuth 2.0 Actually Works: A Simple Guide With Real-World Examples? by @soma_81597 https://t.co/3TunIRSVmk
- Sep 24, 2026
This is the most incredible system design practice platform I have used in 2026 by @soma_81597 https://t.co/fB6WT3cOzm https://t.co/g9CyvrCGKQ
- Aug 28, 2026
My boss just sent me a Slack message that says "hey do you have a sec?" No context. Just the digital equivalent of a tap on the shoulder before an execution. I replied "sure, what's up?" two minutes ago. The little indicator says he's typing. He's been typing for three solid minutes. What could possibly take three minutes to type? Are we restructuring the entire org chart? Am I being fired via a multi-paragraph manifesto? I checked his calendar and he has a meeting with HR at noon. My heart rate is currently higher than it was during my last stress test. He finally hit send. "Do you know how to convert a PDF to a Word doc?" I'm going to bill the company for my future cardiology appointments.
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 10 interactions against 87K followers, an engagement rate of 0.011%. Measured over 14 original posts, its engagement rate beats 19% of 21,185 tracked accounts of a similar size. That is a reason to look at how the audience behaves - reply depth, saves, whether the followers are recent - rather than a conclusion about it on its own. Posts are seen about 2.8K times each, and 0.359% of those impressions turn into an interaction. That is about 3.20% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 2.7 posts a day over the last 30 days, with activity on roughly 47% of days. Most posts go out around 01:00 UTC, and Saturday is the busiest day of the week. Of the 14 posts sampled, 36% carry an image or video, 7% are part of a thread and 57% link out. The account's strongest tracked post pulled 7.9K interactions, about 785x its own typical post. Recurring topics include #courses, #onlineresources, #bestofjavarevisited.
- What is Javarevisited's engagement rate on X?
- Javarevisited (@javarevisited) has an engagement rate of 0.011%, based on the median interactions across 14 original posts from the last 30 days against 86,927 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.011%, Javarevisited sits above the 10th percentile of the 212,741 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 @javarevisited have real engagement?
- Its engagement rate beats 19% of the tracked X accounts closest to it in follower count (21,185 accounts), which puts it in the bottom 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 @javarevisited post?
- Most posts go out around 01:00 UTC, and Saturday is its busiest day, at roughly 2.67 posts per day across the measured window.