Microsoft Research engagement report
@MSFTResearch - 555K followers on X
Measured over 12 original posts from a 30-day window, last computed on August 27, 2026.
Engagement
A typical post picks up 104 interactions against 555K followers, an engagement rate of 0.019%. Measured over 12 original posts, its engagement rate beats 42% of 3,758 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 18K times each, and 0.586% of those impressions turn into an interaction. That is about 3.18% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.47 posts a day over the last 30 days, though only 33% of days saw any activity at all. Most posts go out around 16:00 UTC, and Monday is the busiest day of the week. Of the 12 posts sampled, 100% carry an image or video and 92% link out. The account's strongest tracked post pulled 318 interactions, about 3.1x its own typical post.
Measured over 12 original posts from a 30-day window, last computed on August 27, 2026.
Compared with accounts its own size
Microsoft Research's engagement rate beats 42% of the tracked X accounts closest to it in follower count (3,758 accounts, accounts of similar size (decile 8 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 38% 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 0.019%, Microsoft Research sits above the 25th percentile of the 36,521 accounts in this comparison. That places it in the below the median band, which runs 0.012% to 0.08%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.002% |
| 25th percentile | 0.012% |
| 50th percentile | 0.08% |
| 75th percentile | 0.434% |
| 90th percentile | 2.10% |
| 99th percentile | 160.7% |
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 16:00 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% | 50K |
| 01:00 UTC | -2% | 51K |
| 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% | 60K |
| 09:00 UTC | -3% | 69K |
| 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% | 100K |
| 16:00 UTC | -3% | 97K |
| 17:00 UTC | -2% | 90K |
| 18:00 UTC | -1% | 84K |
| 19:00 UTC | -2% | 79K |
| 20:00 UTC | -1% | 74K |
| 21:00 UTC | -1% | 66K |
| 22:00 UTC | -2% | 57K |
| 23:00 UTC | -2% | 51K |
Show engagement by day of week as a table
| Day | Vs author median | Posts |
|---|---|---|
| Sunday | +4% | 230K |
| Monday | 0% | 286K |
| Tuesday | -2% | 276K |
| Wednesday | -1% | 251K |
| Thursday | -1% | 244K |
| Friday | -3% | 252K |
| Saturday | +3% | 227K |
Best tweets
- Aug 3, 20263.1x their median
Orchard is an open-source framework for the research community to train and evaluate AI agents across task types. It reduces complexity while supporting strong performance from smaller models by enabling researchers to reuse the same infrastructure. https://t.co/uxVNQdB1fQ https://t.co/lcTRD9gMdO
- Jul 30, 20262.9x their median
LLMs do not get smarter just by remembering more. EvoLib turns experience into evolving knowledge, taking reusable skills and insights that help models learn and adapt across tasks long after deployment. https://t.co/FR89BgW6Vx https://t.co/CiNfXGb3ux
- Aug 3, 20261.6x their median
Small language models learn to negotiate with SocialRL, PazaBench V2 expands speech AI evaluation across African languages, and EvoLib helps agents turn experience into knowledge. Plus: new methods for more reliable A/B testing and advances in AI-driven precision oncology. https://t.co/0N1CGFXZfj
- Jul 30, 2026
Computer-use AI agents struggle with multi-step workflows like email and customer support. Echoverse trains agents in realistic environments rather than simply providing more training tasks, helping them improve as the tasks, tests, and environments evolve. https://t.co/8STvmt2miZ
- Aug 4, 2026
Can AI learn pathology through clinical dialogue? Introducing PRISM2, a multimodal foundation model trained on pathology images and language from real pathology reports. Using simple question-answering, PRISM2 matches specialized cancer-detection systems across several benchmark tasks without requiring a separate model for each task. https://t.co/nFcMESL9Gh
- Aug 24, 2026
Skala 1.1, the updated deep-learning exchange-correlation functional from Microsoft Research, provides greater accuracy, expanded accessibility across the computational chemistry ecosystem, and a living benchmark to track computational performance. https://t.co/70KQmwBekl https://t.co/fuMvzUSEKf
- Jul 22, 2026
MagenticLite's models are now fully open source. MagenticBrain and Fara 1.5, previously available on Microsoft Foundry, are live on Hugging Face with open weights. The app, the harness, and every model in the stack are now open. https://t.co/yAgXdiLy37
- Jun 29, 2026
AI agents can't remember past conversations. They must constantly reload or retrieve context, which grows less efficient as tasks get longer and more complex. Memora solves this with a scalable memory system separating what’s stored from how it's retrieved: https://t.co/XZfOqbA705
- Jun 30, 2026
AI agents often fail because their instructions, or skills, are manually modified with no guarantee of improvement. Learn how SkillOpt turns skill editing into a training process, making agent behavior more reliable without changing model weights: https://t.co/6o0O8c3d4x https://t.co/TlfpieGJ8m
- Jul 9, 2026
Aurora 1.5 adds 22 more variables, hourly temporal resolution, and probabilistic ensemble forecasting to the Aurora foundation model, making it more useful for real-world weather, climate, and energy applications. https://t.co/GnbCNxEKME https://t.co/2Dxoc3MVAd
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 104 interactions against 555K followers, an engagement rate of 0.019%. Measured over 12 original posts, its engagement rate beats 42% of 3,758 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 18K times each, and 0.586% of those impressions turn into an interaction. That is about 3.18% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.47 posts a day over the last 30 days, though only 33% of days saw any activity at all. Most posts go out around 16:00 UTC, and Monday is the busiest day of the week. Of the 12 posts sampled, 100% carry an image or video and 92% link out. The account's strongest tracked post pulled 318 interactions, about 3.1x its own typical post.
- What is Microsoft Research's engagement rate on X?
- Microsoft Research (@MSFTResearch) has an engagement rate of 0.019%, based on the median interactions across 12 original posts from the last 30 days against 554,771 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.019%, Microsoft Research sits above the 25th percentile of the 36,521 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 @MSFTResearch have real engagement?
- Its engagement rate beats 42% of the tracked X accounts closest to it in follower count (3,758 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 @MSFTResearch post?
- Most posts go out around 16:00 UTC, and Monday is its busiest day, at roughly 0.47 posts per day across the measured window.