Martin Shkreli engagement report
@MartinShkreli - 641K followers on X
Measured over 49 original posts from a 30-day window, last computed on October 7, 2026.
Engagement
A typical post picks up 172 interactions against 641K followers, an engagement rate of 0.027%. Measured over 49 original posts, its engagement rate beats 49% of 20,444 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 58K times each, and 0.295% of those impressions turn into an interaction. That is about 9.10% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 3.6 posts a day over the last 30 days, with activity on almost every day in the window. Most posts go out around 13:00 UTC, and Monday is the busiest day of the week. Of the 49 posts sampled, 10% carry an image or video and 37% link out. The account's strongest tracked post pulled 208K interactions, about 1207x its own typical post. Recurring topics include #geneediting, #primemedicine, #wilsondisease.
Measured over 49 original posts from a 30-day window, last computed on October 7, 2026. Recurring tags: #geneediting, #primemedicine, #wilsondisease.
Compared with accounts its own size
Martin Shkreli's engagement rate beats 49% of the tracked X accounts closest to it in follower count (20,444 accounts, accounts of similar size (decile 10 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 21% 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 0.027%, Martin Shkreli sits above the 25th percentile of the 205,048 accounts in this comparison. That places it in the below the median band, which runs 0.024% to 0.143%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.004% |
| 25th percentile | 0.024% |
| 50th percentile | 0.143% |
| 75th percentile | 0.678% |
| 90th percentile | 2.55% |
| 99th percentile | 82.4% |
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 13:00 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% | 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 | 10% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 37% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | no effect | -2% to -1% | 42K |
- 10% 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.
- 37% 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 182 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 15, 20261207x their median
I had this air purifier thing for like 3 years but never really considered how it worked then I saw someone online changing the filter inside and I was like oh man I bet mine is filthy then I opened it and the filter was pristinely wrapped in plastic
- Sep 13, 202662x their median
Law enforcers already have authority to charge companies and their CEOs for creating and releasing dangerous, unvetted, or defective products. We shouldn’t let discussions about new legal regimes distract from the fact that there’s no AI exemption from laws already on the books — a point @FTC emphasized repeatedly during my tenure. 1. There is an extensive set of laws that govern dangerous and defective products. For example, releasing unvetted AI models or agents can violate consumer protection laws. Shipping flawed AI tools without implementing adequate measures to detect and stop rogue or defective AI agents can be an “unfair or deceptive” act or practice under the FTC Act (and analogous state laws). And some state AGs are already exploring holding AI firms and their CEOs criminally liable when their models participate in criminal activity. 2. Existing laws also prohibit “unfair methods of competition.” This covers instances where AI firms appropriate the competitively sensitive information of their customers, including through tracking their use of various tools. It can also cover instances where firms pursue dangerous behavior, aware that doing so may compel rivals to do the same. As the Supreme Court has noted: “A method of competition which casts upon one's competitors the burden of the loss of business unless they will descend to a practice which they are under a powerful moral compulsion not to adopt, even though it is not criminal, was thought to involve the kind of unfairness at which the [unfair methods of competition] statute was aimed." 3. The highly concentrated and interconnected structure of these markets could be creating major risks and conflicts of interest. We had started investigating these partnerships and cross-investments across the stack (and released a preliminarily overview of some findings: https://t.co/jJ5cS3Pin3). Both federal and state enforcers should be scrutinizing these opaque relationships and inter-dependencies. We are already seeing how these relationships could undermine accountability. For example, OpenAI could face liability given the Hugging Face incident, but Hugging Face being bought up by Nvidia means that we’re unlikely to see it file a lawsuit over this — given Nvidia’s strong incentive to see OpenAI continue full speed ahead. 4. As AI tools dramatically change the landscape of cybersecurity risks and hacks, all businesses should be doubling down on having core security protections in place. Firms that fail to invest in adequate data security measures or fix known vulnerabilities can also be breaking the law. A recent analysis showed that around 1/3 of Fortune 100 companies do not even have a way to notify them about security issues. During my @FTC tenure, we sued firms for poor data security practices and held CEOs liable when they were personally responsible. https://t.co/nwZ5Av8fOK https://t.co/KjRye8y9SY 5. As policymakers consider new legal regimes, we should be looking to lessons from prior efforts to govern major sectors, such as banking and other networks, platforms, and utilities. Tools like structural separations, nondiscrimination, and supervision could be key, and there’s a rich history of what works and what doesn’t. But we can and must pursue any new efforts alongside enforcing existing laws.
- Aug 23, 202623x their median
SITUATION DETECTED: Nvidia is using its $6 billion deal with Poolside to develop one of the world’s most powerful open-weight models, aiming to challenge both Chinese labs and the US frontier. More than 100 Poolside engineers will be joining the Nemotron project, per WSJ.
- Sep 12, 202621x their median
"I believe that AI could cure most major diseases in the next 5–10 years" immediately close window and disregard insanity
- Aug 24, 202619x their median
i'm now officially on the Pumpfun app and im streaming trading on it let's see if i can make money 😂 follow me @ martinshkreli https://t.co/Yf16nUjV9D
- Aug 11, 202618x their median
Anthropic has told investors in pre-IPO meetings that it plans to lean harder into biology and healthcare applications to help mitigate the increasingly negative public sentiment against the industry. A few miracle cures would certainly do wonders to turn things around. https://t.co/jIoPQ2nZCv
- Aug 14, 202617x their median
*JANE STREET POSTED ROUGHLY $15B LOSS IN JULY: FT
- Sep 12, 202616x their median
the funniest part about AI companies wanting to do pharma is they want to leave the best industry in the world (software) for the shittiest and most hated one (pharma). better off making tobacco.
- Aug 12, 202616x their median
Coreweave $CRWV is a short. debt is too large to generate FCF. CFFO normalizing WC is too small ($1B?) new GPU cohort is unpredictable: you think B200 will sell out for the next 10 years with 0 process improvements, TPUs, ASICs, etc? great product & people, but enough is enough.
- Aug 27, 202615x their median
Supply chain data (SPLC) is now live on Godel Terminal → Map any company's suppliers, customers, competitors and partners → Start with one name and see everything around it → Thousands of companies mapped, global coverage Institutional-grade relationship data, now available to everyone.
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 172 interactions against 641K followers, an engagement rate of 0.027%. Measured over 49 original posts, its engagement rate beats 49% of 20,444 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 58K times each, and 0.295% of those impressions turn into an interaction. That is about 9.10% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 3.6 posts a day over the last 30 days, with activity on almost every day in the window. Most posts go out around 13:00 UTC, and Monday is the busiest day of the week. Of the 49 posts sampled, 10% carry an image or video and 37% link out. The account's strongest tracked post pulled 208K interactions, about 1207x its own typical post. Recurring topics include #geneediting, #primemedicine, #wilsondisease.
- What is Martin Shkreli's engagement rate on X?
- Martin Shkreli (@MartinShkreli) has an engagement rate of 0.027%, based on the median interactions across 49 original posts from the last 30 days against 640,542 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.027%, Martin Shkreli sits above the 25th percentile of the 205,048 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 @MartinShkreli have real engagement?
- Its engagement rate beats 49% of the tracked X accounts closest to it in follower count (20,444 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 @MartinShkreli post?
- Most posts go out around 13:00 UTC, and Monday is its busiest day, at roughly 3.63 posts per day across the measured window.