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Geert Vanden Bossche engagement report

@GVDBossche - 291K followers on X

Measured over 14 original posts from a 30-day window, last computed on October 20, 2026.

Engagement

Middle of its size range
Per follower
0.066%
of 291K followers
Per impression
1.14%
17K views on a typical post
Reach
5.77%
of its followers see a post
Typical post
192
interactions (median)
Saved
0.295%
50 bookmarks on a typical post
Posting rate
1.43/day
active 37% of days
Peak time
19:00 UTC
Tuesday

A typical post picks up 192 interactions against 291K followers, an engagement rate of 0.066%. Measured over 14 original posts, its engagement rate beats 51% 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 17K times each, and 1.14% of those impressions turn into an interaction. That is about 5.77% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.4 post a day over the last 30 days, though only 37% of days saw any activity at all. Most posts go out around 19:00 UTC, and Tuesday is the busiest day of the week. Of the 14 posts sampled, 21% carry an image or video, 21% are part of a thread and 86% link out. The account's strongest tracked post pulled 9.7K interactions, about 51x its own typical post.

Measured over 14 original posts from a 30-day window, last computed on October 20, 2026.

Compared with accounts its own size

Geert Vanden Bossche's engagement rate beats 51% of the tracked X accounts closest to it in follower count (20,444 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 46% 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 0.066%, Geert Vanden Bossche sits above the 25th percentile of the 205,374 accounts in this comparison. That places it in the below the median band, which runs 0.024% to 0.143%.

p100.004%
p250.024%
p50 (median)0.143%
p750.678%
p902.55%
p9982.4%
Engagement rate as a share of followers, across the 205,374 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 22,897 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 19:00 UTC, and Tuesday 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: 19:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 111%Busiest hour: 19:00 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: Tuesday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 111%Busiest day: Tuesday
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 video21% of posts+111%+108% to +115%34K
Outbound link86% of posts-41%-42% to -40%32K
Typical length-+15%+14% to +16%32K
  • 21% 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.
  • 86% of its posts carry a link off X. Across the catalog, posts with an outbound link run 41% below the same accounts' other posts, so a large share of this account's output sits in the weakest bucket we measure.
  • Its average post runs 489 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

  • Aug 6, 202651x their median

    We got played. Fauci was yelled at in the Senate then they turned around and approved Covid shot pusher Erica Schwartz as CDC Director and the FDA approved the mRNA flu shot. Senators Moreno & Paul, who I like a lot, voted Yea and the margin was 2 votes. https://t.co/kIxkbhwtbZ

    6.3K2.4K680325333K viewsView on X
  • Oct 13, 202624x their median

    Beste volgers, ik heb besloten om mij terug te trekken van het publieke toneel. Ik beschouw mijn taak als grotendeels volbracht en voel me geroepen om mijn leven een nieuwe wending te geven. Ik geef daar wat meer uitleg over in deze bijdrage, een soort afscheidsbrief. Het virus blijft. De viroloog vertrekt. https://t.co/dKzr0yelxk

    3.6K4805103481K viewsView on X
  • Oct 13, 202623x their median

    Dear followers, I have decided to withdraw from the public stage. I consider my task largely accomplished and feel called to give my life a new direction. I explain this further in this post, which is a kind of farewell letter. The Virus Stays. The Virologist Leaves. https://t.co/fpcq1y8LQ8

    3.5K4834763896K viewsView on X
  • Aug 4, 202616x their median

    "Most published research findings are false." Say that out loud in a hospital and you'd get laughed out of the room. That's the actual title of a paper by John Ioannidis at Stanford, whom Dr. Aseem Malhotra calls the most cited medical researcher alive. The greater the financial interest in a field, the less likely its research is to be true. Doctors treat the New England Journal of Medicine, JAMA, and The Lancet like biblical truth. They don't realize how much of it is corrupted by vested interests. Dr. Malhotra spent years treating those journals as gospel. Then he realized what he was actually reading: studies bought and shaped by the people who profit from them. He isn't saying doctors are bad. He's saying they're being manipulated and don't know it.

    2.0K8307891176K viewsView on X
  • Jun 8, 202315x their median

    Ten-part video series summarizing my new book can be found here: https://t.co/yJfRx645aC Order the book at https://t.co/SXjYGCce3a #covidvacccine #scientificliteracy #pandemic #inescapableimmuneescape https://t.co/TREHu4q76X

    2.0K74612669801K viewsView on X
  • Aug 4, 202613x their median

    HOLY SHITBALLS. @brownstoneinst @jeffreytucker @POTUS @SecKennedy @SenRonJohnson @RandPaul @FBIDirectorKash Robert Gallo (yes, HIV Gallo) returned an email to Francis Collins on May 3, 2020, and explicitly warned him of the perils of using glycosylated spike proteins in vaccines. Collins (and Fauci) IGNORED HIM. https://t.co/yOIGn5X2pJ

    1.7K733574082K viewsView on X
  • Oct 6, 20268.7x their median

    This can NOT be denied any longer: First Study Finds COVID-19 "Vaccines" Increase Risk of Multiple Cancers: https://t.co/1BK8LztXTM Second Study Finds COVID-19 "Vaccines" Increase Risk of Multiple Cancers: https://t.co/BY9nTeOJh9 U.S. Government Cancer Data Shows Early-Onset Cancers Surged During Mass mRNA Vaccination: https://t.co/9A31c3iRX3 CDC data shows 138,000+ excess cancer deaths in the U.S. since the beginning of mass mRNA vaccination: https://t.co/YTfMP2mk0y Systematic Review Documents 300+ Peer-Reviewed COVID Shot Turbo Cancer Cases Across 27 Countries: https://t.co/Pbg9SuY27q mRNA "Vaccine" Genomic integration Demonstrated: https://t.co/ilQOHlugFy mRNA Injections Induce Severe, Long-Lasting Genetic Disruption Linked to Cancer and Chronic Disease: https://t.co/UwSI1tJvdg mRNA "Vaccine" Spike Protein Detected in Both the Cytoplasm and Nuclei of Metastatic Breast Cancer Cells: https://t.co/2PMNUs8wCq First Peer-Reviewed Paper Defines COVID-19 Vaccine-Induced Turbo Cancer: https://t.co/mj9f9wkLhG 17 Ways mRNA Shots Induce Cancer, According to 100 Studies: https://t.co/CefBnYcGCg

    1.0K556485847K viewsView on X
  • Aug 5, 20266.3x their median

    Early in the COVID-19 pandemic, scientists noticed that a SARS-CoV-2 infection can “wake up” other, dormant viruses already present in the body. A new study extends those and subsequent observations, documenting viral reactivation for a cohort of more than 1000 patients hospitalized with COVID-19 before mid-2021. The findings provide a detailed picture of the hidden viruses that become active at different points of a SARS-CoV-2 infection, and link reactivation of some of them to more severe COVID-19 and to lingering symptoms, such as fatigue, that are the hallmark of Long Covid. Learn more: https://t.co/hPoWUNBcLq

    791350313260K viewsView on X
  • Aug 24, 20266.2x their median

    Yet more evidence suggests that repeated mRNA vaccination induces a progressive increase in S-specific IgG4 Abs while higher IgG4 Ab levels are associated with an increased risk of subsequent vaccine-breakthrough infection (VBTI). VBTIs, in turn, provide the antigenic stimulus for immune refocusing. This already explains why mRNA vaccination drives immune refocusing and therefore can never be considered either safe or effective! https://t.co/u6jkB44ELw

    820303292930K viewsView on X
  • Oct 12, 20265.4x their median

    👀He wanted us silenced. Now he says that public health got it wrong. Dr. Zubin "ZDogg" Damania once described people who questioned vaccines as “stupid,” “delusional,” and deserving of shame and silencing. In a recent video, he struck a very different tone: “There’s no vaxxers and anti-vaxxers. They’re just people trying to do the right thing for themselves and their kids.” Watch the old and new clips side by side... Del has an invite: “ZDogg, your place or mine? Let’s do this.”

    745207671956K 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 192 interactions against 291K followers, an engagement rate of 0.066%. Measured over 14 original posts, its engagement rate beats 51% 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 17K times each, and 1.14% of those impressions turn into an interaction. That is about 5.77% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.4 post a day over the last 30 days, though only 37% of days saw any activity at all. Most posts go out around 19:00 UTC, and Tuesday is the busiest day of the week. Of the 14 posts sampled, 21% carry an image or video, 21% are part of a thread and 86% link out. The account's strongest tracked post pulled 9.7K interactions, about 51x its own typical post.

What is Geert Vanden Bossche's engagement rate on X?
Geert Vanden Bossche (@GVDBossche) has an engagement rate of 0.066%, based on the median interactions across 14 original posts from the last 30 days against 291,108 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.066%, Geert Vanden Bossche sits above the 25th percentile of the 205,374 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 @GVDBossche have real engagement?
Its engagement rate beats 51% 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 @GVDBossche post?
Most posts go out around 19:00 UTC, and Tuesday is its busiest day, at roughly 1.43 posts per day across the measured window.

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