Digg engagement report
@digg - 1.1M followers on X
Measured over 22 original posts from a 30-day window, last computed on August 31, 2026.
Engagement
A typical post picks up 1.8K interactions against 1.1M followers, an engagement rate of 0.162%. Measured over 22 original posts, its engagement rate beats 80% of 3,774 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 265K times each, and 0.686% of those impressions turn into an interaction. That is about 23.6% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 3.1 posts a day over the last 30 days, with activity on roughly 53% of days. Most posts go out around 14:00 UTC, and Monday is the busiest day of the week. Of the 22 posts sampled, 50% carry an image or video and 27% link out. The account's strongest tracked post pulled 22K interactions, about 12x its own typical post.
Measured over 22 original posts from a 30-day window, last computed on August 31, 2026.
Compared with accounts its own size
Digg's engagement rate beats 80% of the tracked X accounts closest to it in follower count (3,774 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 41% 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 0.162%, Digg sits above the 50th percentile of the 36,654 accounts in this comparison. That places it in the above the median band, which runs 0.08% to 0.433%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.002% |
| 25th percentile | 0.012% |
| 50th percentile | 0.08% |
| 75th percentile | 0.433% |
| 90th percentile | 2.10% |
| 99th percentile | 160.5% |
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 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.
Show engagement by hour posted, utc as a table
| Hour (UTC) | Vs author median | Posts |
|---|---|---|
| 00:00 UTC | -1% | 51K |
| 01:00 UTC | -2% | 52K |
| 02:00 UTC | -3% | 50K |
| 03:00 UTC | -4% | 53K |
| 04:00 UTC | -6% | 43K |
| 05:00 UTC | -4% | 42K |
| 06:00 UTC | -4% | 48K |
| 07:00 UTC | -5% | 52K |
| 08:00 UTC | -4% | 61K |
| 09:00 UTC | -3% | 70K |
| 10:00 UTC | -2% | 72K |
| 11:00 UTC | -3% | 78K |
| 12:00 UTC | -2% | 86K |
| 13:00 UTC | -2% | 94K |
| 14:00 UTC | -4% | 97K |
| 15:00 UTC | -2% | 101K |
| 16:00 UTC | -3% | 98K |
| 17:00 UTC | -2% | 91K |
| 18:00 UTC | -1% | 85K |
| 19:00 UTC | -1% | 80K |
| 20:00 UTC | -1% | 74K |
| 21:00 UTC | -1% | 66K |
| 22:00 UTC | -1% | 57K |
| 23:00 UTC | -2% | 52K |
Show engagement by day of week as a table
| Day | Vs author median | Posts |
|---|---|---|
| Sunday | +4% | 231K |
| Monday | 0% | 288K |
| Tuesday | -2% | 278K |
| Wednesday | -1% | 251K |
| Thursday | -1% | 245K |
| Friday | -3% | 253K |
| Saturday | +3% | 227K |
Best tweets
- Aug 25, 202612x their median
I’m thinking about banning Claude code at Shopify until they change their mind and read AGENTS.md and .agents/skills etc. Insisting on only reading CLAUDE.md sometimes leads to split brain problems when different team members use different tools. Just unnecessary.
- Aug 14, 202611x their median
We promised open weights for Qwen3.8. Now, time to meet them! 🎉 ⚡ Qwen3.8-27B: - A native multimodal dense model. With just 27B parameters, it outperforms Qwen3.7-Plus overall and shines in real-world coding & office workflows. - 262K native context, easily extendable to 1M tokens via YaRN. - Built for builders. Highly efficient, high-quality, and licensed under Apache 2.0. 🚀 The open weights for Qwen3.8-2.4T-A95B (Max-level) have also been released recently. Whether you're shipping lightweight applications with Qwen3.8-27B locally or building agents with Qwen3.8-2.4T-A95B, they're yours now! Download, deploy, and build something we haven't imagined yet. 👀👇 - Hugging Face： https://t.co/4kaAcqYEVj - ModelScope： https://t.co/eRIMZCGkhC
- Aug 21, 20264.2x their median
Our general-purpose coding agent just scored 100% on the ARC-AGI-3 interactive reasoning benchmark. NVIDIA AVO completed all 183 levels across all 25 public environments, figuring out what to do with no instructions, explicit rules, or stated goals. https://t.co/UgROuDrMtn
- Aug 17, 20263.8x their median
New: An "expert witness" in a $61 million lawsuit over an industrial explosion that killed three people and destroyed 200 homes used ChatGPT to write his report for the court. He prompted ChatGPT to "show how 3M is 0% at fault for the explosion at Watson Grinding" https://t.co/FfeSzap8XZ
- Aug 14, 20262.0x their median
GPT 5.6 just solved one of my maths problems that GPT 5.5 insisted for 6 months is unsolvable🤔
- Aug 13, 20262.0x their median
What I'm hearing from ~3 such stories: Meta went too far firing people. They are now doing MASSIVE counter-offers like to those handing in resignations. Some accept it, most just use it for more $$ at New Job, desperate to get out. It was such a predictable outcome btw: https://t.co/MomlsXYlov
- Aug 14, 2026
don't use skills.md or SKILLS or whatever by the way. it's bloat just put everything in an agents.md
- Aug 24, 2026
We discovered that US GDP statistics miss most of the value Nvidia adds to the US economy. As a result, GDP growth has been understated by ~0.3 percentage points over the last year. https://t.co/skgKN3epEG
- Aug 14, 2026
1/ Today, we introduce Faraday, a 27B-parameter AI Scientist that extends the capabilities of coding agents with a layer of scientific intuition. Trained via long-horizon RL, Faraday outperforms Claude Opus 4.8 and GPT-5.5 on the task of replicating research papers. 🧵 https://t.co/nA6ylMNrvj
- Aug 13, 2026
My cofounder Tim, whom you will not find on X, shares some of the strategic thinking behind our latest updates https://t.co/NlS1wE9XX5
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.
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Reading these numbers
A typical post picks up 1.8K interactions against 1.1M followers, an engagement rate of 0.162%. Measured over 22 original posts, its engagement rate beats 80% of 3,774 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 265K times each, and 0.686% of those impressions turn into an interaction. That is about 23.6% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 3.1 posts a day over the last 30 days, with activity on roughly 53% of days. Most posts go out around 14:00 UTC, and Monday is the busiest day of the week. Of the 22 posts sampled, 50% carry an image or video and 27% link out. The account's strongest tracked post pulled 22K interactions, about 12x its own typical post.
- What is Digg's engagement rate on X?
- Digg (@digg) has an engagement rate of 0.162%, based on the median interactions across 22 original posts from the last 30 days against 1,120,580 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.162%, Digg sits above the 50th percentile of the 36,654 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 @digg have real engagement?
- Its engagement rate beats 80% of the tracked X accounts closest to it in follower count (3,774 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 @digg post?
- Most posts go out around 14:00 UTC, and Monday is its busiest day, at roughly 3.13 posts per day across the measured window.