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Dr. Deepti Gurdasani engagement report

@dgurdasani1 - 122K followers on X

Measured over 3 original posts from a 30-day window, last computed on October 5, 2026.

Engagement

Per follower
0.229%
of 122K followers
Per impression
0.828%
34K views on a typical post
Reach
27.7%
of its followers see a post
Typical post
279
interactions (median)
Saved
0.134%
45 bookmarks on a typical post
Posting rate
0.67/day
active 37% of days
Peak time
13:00 UTC
Wednesday

Early reading. We have captured 3 original posts for this account, below the 8 we require before treating a median as settled. The numbers above describe what we have seen so far, not a finished profile of the account.

A typical post picks up 279 interactions against 122K followers, an engagement rate of 0.229%. Posts are seen about 34K times each, and 0.828% of those impressions turn into an interaction. That is about 27.7% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.67 post a day over the last 30 days, though only 37% of days saw any activity at all. Most posts go out around 13:00 UTC, and Wednesday is the busiest day of the week. Of the 3 posts sampled, 100% carry an image or video. The account's strongest tracked post pulled 8.9K interactions, about 32x its own typical post. Only 3 original posts have been captured so far, fewer than the 8 posts we want behind a median before treating it as settled. Read the figures above as an early measurement of this account, not as a finished profile of it.

Measured over 3 original posts from a 30-day window, last computed on October 5, 2026.

Where this sits in the catalog

At 0.229%, Dr. Deepti Gurdasani sits above the 50th percentile of the 205,261 accounts in this comparison. That places it in the above the median band, which runs 0.143% to 0.678%.

p100.004%
p250.024%
p50 (median)0.143%
p750.678%
p902.55%
p9982.4%
Engagement rate as a share of followers, across the 205,261 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 22,894 times apart and a linear axis would flatten everything below the median into a single point.
Show the percentile table
Engagement rate percentiles
PercentileEngagement rate
10th percentile0.004%
25th percentile0.024%
50th percentile0.143%
75th percentile0.678%
90th percentile2.55%
99th percentile82.4%

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 Wednesday 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.

Engagement by hour posted, UTCTwenty-four bars, one per UTC hour. Each bar shows how posts published in that hour compare with their own authors' median engagement. Bars above the centre line ran higher than the median, bars below ran lower. A marker flags Busiest hour: 13:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 111%Busiest hour: 13:00 UTC
Show engagement by hour posted, utc as a table
Engagement by hour posted, UTC
Hour (UTC)Vs author medianPosts
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 UTC0%116K
22:00 UTC-2%100K
23:00 UTC-1%90K
Engagement by day of weekSeven bars, one per weekday, Sunday first. Each bar shows how posts published on that day compare with their own authors' median engagement. Bars above the centre line ran higher than the median, bars below ran lower. A marker flags Busiest day: Wednesday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 111%Busiest day: Wednesday
Show engagement by day of week as a table
Engagement by day of week
DayVs author medianPosts
Sunday+5%393K
Monday+1%483K
Tuesday-2%520K
Wednesday-3%472K
Thursday-2%430K
Friday-3%447K
Saturday+2%393K
See what moves engagement across the whole catalogWhat counts as a good engagement rate at this size

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.

This account's posting mix compared with catalog-wide effects
FormatThis accountCatalog effect95% intervalAccounts behind it
Image or video100% of posts+111%+108% to +115%34K
Outbound link0% of posts-41%-42% to -40%32K
Typical length-no effect-2% to -1%42K
  • 100% 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.
  • 0% 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 272 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

  • Oct 14, 202032x their median

    NEW Correspondence—80+ researchers warn that a so-called #herdimmunity approach to managing #COVID19 is “a dangerous fallacy unsupported by the scientific evidence” #WCPH2020 https://t.co/2gTtklAkwx https://t.co/q4YNZFJM22

    4.7K3.3K233738View on X
  • Aug 22, 202617x their median

    The Ghent professor who hired Cofnas through the back door has been part of what looks like a resurgence of 'race science' in various pockets across Europe. Belgian journalists have been onto this for a while. https://t.co/hpHqtRukkF

    3.2K1.4K363474K viewsView on X
  • Aug 21, 202613x their median

    Gotta love the white academics talking about academic freedom/standards/integrity now that Cofnas was suspended. A eugenicist (backed by powerful networks) led a campaign against a Black scholar calling him "retarded", "illiterate", hounding him to death. So let's talk standards

    2.8K7201123190K viewsView on X
  • Aug 30, 20269.4x their median

    A new Substack article by @Cartrarian provides very convincing evidence that Jason Arday never had autism. The article shows that: ➡️Arday never mentioned he had autism until 2018. Even in his 2015 dissertation, he merely says he had "learning difficulties." ➡️The diagnostic history Arday reported was contradictory and anachronistic. Some of the labels he claims he had as a child were rare or nonexistent at the time. Other diagnoses he claims to have had are contradictory and cannot be present in the same person. ➡️Arday also contradicted himself in discussing when he learned about his diagnosis. Sometimes he says he knew at age 3, but he also claimed to have not been told until his mid-30s. ➡️Arday didn't seem to understand what autism is. Sometimes he said it's a "hybrid" diagnosis, and at other times Arday said it was a type of other disabilities. Hhe even said it was "a kind of intellectual disability," which is absurdly wrong. This article exposes (and refutes) new lies from Arday that were previously unnoticed (or perhaps less publicized): ➡️Arday claimed to have been in a longitudinal study that does not exist. ➡️Arday said he attended a special needs school, but it is now documented fact that he attended the mainstream Heathbrook Primary School. ➡️New discrepancies in Arday's vita. It's a long read, but that's because Arday told a lot of lies, and Cartrarian is careful to document and debunk them. It's definitely worth reading. https://t.co/jZ7FHeGKS5

    2.0K30917882438K viewsView on X
  • Aug 21, 20263.1x their median

    I've signed this letter in support of Nathan Cofnas. Whatever one thinks of Cofnas, academic whistleblowers should be protected from retaliation. Liberal-democratic rights are either universal or they are nothing. https://t.co/kIqkdQmPjh

    651641252392K viewsView on X
  • Sep 30, 20263.0x their median

    Human rights lawyer @WolfgangKaleck represents the family of Patrice Lumumba, the first Congolese prime minister, who was assassinated in a U.S.- and Belgian-backed coup. “This is a story of the West preventing democratically elected leaders in the Global South from distributing the goods of their country to the peoples of the country,” says Kaleck.

    54429051236K viewsView on X
  • Sep 9, 2026

    Now you see why they want a “FINRA for AI” model. It allows them to buy the regulator. Coefficient Giving, cofounded by Daniela Amodei’s husband (since left) and funded by Moskovitz (who invested in Anthropic), is spending hundreds of millions on ai safety orgs. Like Redwood. https://t.co/ZdooUpeCCX

    2213912727K viewsView on X
  • Aug 20, 2026

    If you are a UK based Black academic/scholar and you are looking for a space to process, please let me know and I will DM you something.

    189641327.9K viewsView on X
  • Sep 3, 2026

    Allegations of bullying and misconduct raised against James Orr, Professor of Divinity at Cambridge University Allegations upheld, but resulted in no disciplinary action – even though the student was lied to and told that it had https://t.co/dylnnUoeLu

    1826851227K viewsView on X
  • Sep 23, 2026

    This is mind blowing. OpenAI hacked private Australian Medicare files… and didn’t say a word about it to the government. Article in replies. https://t.co/y96aztFhIG

    16062201234K viewsView on X

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 279 interactions against 122K followers, an engagement rate of 0.229%. Posts are seen about 34K times each, and 0.828% of those impressions turn into an interaction. That is about 27.7% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.67 post a day over the last 30 days, though only 37% of days saw any activity at all. Most posts go out around 13:00 UTC, and Wednesday is the busiest day of the week. Of the 3 posts sampled, 100% carry an image or video. The account's strongest tracked post pulled 8.9K interactions, about 32x its own typical post. Only 3 original posts have been captured so far, fewer than the 8 posts we want behind a median before treating it as settled. Read the figures above as an early measurement of this account, not as a finished profile of it.

What is Dr. Deepti Gurdasani's engagement rate on X?
Dr. Deepti Gurdasani (@dgurdasani1) has an engagement rate of 0.229%, based on the median interactions across 3 original posts from the last 30 days against 121,626 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.229%, Dr. Deepti Gurdasani sits above the 50th percentile of the 205,261 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 @dgurdasani1 have real engagement?
There is not yet enough sample to rank this account against others of its size.
When does @dgurdasani1 post?
Most posts go out around 13:00 UTC, and Wednesday is its busiest day, at roughly 0.67 posts per day across the measured window.

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