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Vir Das engagement report

@thevirdas - 7.2M followers on X

Measured over 34 original posts from a 30-day window, last computed on October 7, 2026.

Engagement

Middle of its size range
Per follower
0.005%
of 7.2M followers
Per impression
0.954%
36K views on a typical post
Reach
0.5%
of its followers see a post
Typical post
340
interactions (median)
Saved
0.036%
13 bookmarks on a typical post
Posting rate
1.53/day
active 57% of days
Peak time
04:00 UTC
Saturday

A typical post picks up 340 interactions against 7.2M followers, an engagement rate of 0.005%. Measured over 34 original posts, its engagement rate beats 26% of 15,519 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 36K times each, and 0.954% of those impressions turn into an interaction. That is about 0.499% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.5 posts a day over the last 30 days, with activity on roughly 57% of days. Most posts go out around 04:00 UTC, and Saturday is the busiest day of the week. Of the 34 posts sampled, 53% carry an image or video, 9% are part of a thread and 15% link out. The account's strongest tracked post pulled 166K interactions, about 489x its own typical post.

Measured over 34 original posts from a 30-day window, last computed on October 7, 2026.

Compared with accounts its own size

Vir Das's engagement rate beats 26% of the tracked X accounts closest to it in follower count (15,519 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 48% 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 0.005%, Vir Das sits above the 10th percentile of the 156,027 accounts in this comparison. That places it in the bottom 25% band, which runs below 0.022%.

p100.003%
p250.022%
p50 (median)0.127%
p750.604%
p902.32%
p9983.1%
Engagement rate as a share of followers, across the 156,027 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 25,983 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 percentile0.003%
25th percentile0.022%
50th percentile0.127%
75th percentile0.604%
90th percentile2.32%
99th percentile83.1%

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 04:00 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.

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: 04:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 111%Busiest hour: 04:00 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: Saturday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 111%Busiest day: Saturday
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 video53% of posts+111%+108% to +115%34K
Outbound link15% of posts-41%-42% to -40%32K
Typical length-+15%+14% to +16%32K
  • 53% 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.
  • 15% 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 310 characters, which falls in the over 280 characters band. Across the catalog, posts over 280 characters run 15% above the same accounts' other posts.

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

  • Jul 31, 2026489x their median

    Milo the dinosaur 🦖 🤣🫶 https://t.co/5xOXnp2l9V

    153K11K1.0K8265.9M viewsView on X
  • Jul 22, 2026162x their median

    Man I love Republic TV. You have to keep up ❤️ https://t.co/0nfOIPdKUL

    45K8.4K8584241.9M viewsView on X
  • Jul 25, 2026124x their median

    Thank you PM for NOT firing Pradhan ji two weeks ago. It gave us enough time for: 1. The end of godi media 2. A million funny memes 3. A thousand pictures of courage 4. The rise of a dozen new young political leaders 5. “56 inch ka chhota bandar”

    35K6.9K379103402K viewsView on X
  • Aug 1, 202685x their median

    Have a look at the comments section or dms of any girl in India. Then maybe we can lecture them about their own language.

    24K4.1K9072061.7M viewsView on X
  • Jul 25, 202680x their median

    FRAAANDS!!!!

    25K1.7K36045228K viewsView on X
  • Jul 24, 202673x their median

    Shout out to independent new media journalists by the way. No one would know a damned thing about what’s really happening on ground without you 👊

    22K2.9K14936247K viewsView on X
  • Jul 25, 202638x their median

    I hope you like pancakes, you’re about to see a lot of flipping.

    12K8697039209K viewsView on X
  • Oct 4, 202632x their median

    Ironic how we demand total perfection from the new and inexperienced who ask for legitimate accountability, and nothing from the old and experienced who are legitimately accountable.

    9.1K1.5K23975180K viewsView on X
  • Jul 25, 202621x their median

    Anyone else feel like their eyesight dwindled by 70% in the last week because of screen time?

    6.4K37418825171K viewsView on X
  • Aug 1, 202618x their median

    Narrative is loud, the delhiprompters are aligned.

    5.6K3908214229K 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 340 interactions against 7.2M followers, an engagement rate of 0.005%. Measured over 34 original posts, its engagement rate beats 26% of 15,519 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 36K times each, and 0.954% of those impressions turn into an interaction. That is about 0.499% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.5 posts a day over the last 30 days, with activity on roughly 57% of days. Most posts go out around 04:00 UTC, and Saturday is the busiest day of the week. Of the 34 posts sampled, 53% carry an image or video, 9% are part of a thread and 15% link out. The account's strongest tracked post pulled 166K interactions, about 489x its own typical post.

What is Vir Das's engagement rate on X?
Vir Das (@thevirdas) has an engagement rate of 0.005%, based on the median interactions across 34 original posts from the last 30 days against 7,155,858 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.005%, Vir Das sits above the 10th percentile of the 156,027 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 @thevirdas have real engagement?
Its engagement rate beats 26% of the tracked X accounts closest to it in follower count (15,519 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 @thevirdas post?
Most posts go out around 04:00 UTC, and Saturday is its busiest day, at roughly 1.53 posts per day across the measured window.

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