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The Cinegogue engagement report

@TheCinegogue - 264K followers on X

Measured over 9 original posts from a 30-day window, last computed on September 23, 2026.

Engagement

Middle of its size range
Per follower
0.04%
of 264K followers
Per impression
1.13%
9.4K views on a typical post
Reach
3.55%
of its followers see a post
Typical post
106
interactions (median)
Saved
0.117%
11 bookmarks on a typical post
Posting rate
0.33/day
active 23% of days
Peak time
21:00 UTC
Thursday

A typical post picks up 106 interactions against 264K followers, an engagement rate of 0.04%. Measured over 9 original posts, its engagement rate beats 43% 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 9.4K times each, and 1.13% of those impressions turn into an interaction. That is about 3.55% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.33 posts a day over the last 30 days, though only 23% of days saw any activity at all. Most posts go out around 21:00 UTC, and Thursday is the busiest day of the week. Of the 9 posts sampled, 78% carry an image or video. The account's strongest tracked post pulled 56K interactions, about 188x its own typical post.

Measured over 9 original posts from a 30-day window, last computed on September 23, 2026.

Compared with accounts its own size

The Cinegogue's engagement rate beats 43% 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 0.04%, The Cinegogue 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 21:00 UTC, and Thursday 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: 21:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 111%Busiest hour: 21:00 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: Thursday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 111%Busiest day: Thursday
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 video78% of posts+111%+108% to +115%34K
Outbound link0% of posts-41%-42% to -40%32K
Typical length--8%-9% to -7%41K
  • 78% 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 61 characters, which falls in the under 80 characters band. Across the catalog, posts under 80 characters run 8% below 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

  • Jun 1, 2026188x their median

    AMC had its highest May theater attendance since 2019 🍿 https://t.co/v9ihmiLclJ

    52K2.8K3136105.0M viewsView on X
  • Jun 11, 2026366x their median

    Stevie Knicks, Knickelback and Knickole Kidman https://t.co/CUM4rwBzhJ

    35K2.5K2427654.8M viewsView on X
  • Jun 4, 2026248x their median

    https://t.co/Lkz39xhiw3

    24K1.7K5263257K viewsView on X
  • Jun 2, 202657x their median

    Martin Scorsese has joined a generative AI startup as a partner and advisor. He adds that he has used AI during pre-production to help with storyboarding — “with this tool, I can share what I’m visualizing more clearly & efficiently to my creative team — the production designer, art designer and cinematographer.” (Source: https://t.co/LJlx5ylxvr)

    7.0K4151.1K8.5K8.1M viewsView on X
  • Jun 21, 2026112x their median

    Happy Father’s Day 💕 https://t.co/e0Ti7ZISH7

    8.3K2.0K1931.4K1.1M viewsView on X
  • Jul 4, 202640x their median

    The iconic ending photo in The Shining wasn’t staged with extras. Stanley Kubrick said he couldn’t make them look as good as the people in a real 1921 photo, calling each face “an archetype of the period.” The original image was recently rediscovered in the Getty Images archive. https://t.co/iaoaB7E4iD

    3.9K3453711234K viewsView on X
  • Jun 6, 202638x their median

    https://t.co/Opzui6RgGG

    3.7K249131447K viewsView on X
  • Sep 10, 202632x their median

    The Criterion Collections first ever brick and mortar store https://t.co/6ULIpe3tg3

    3.1K2102355142K viewsView on X
  • Jun 8, 202624x their median

    https://t.co/5xW0kbJwRK

    2.3K1538227K viewsView on X
  • Aug 16, 202617x their median

    don’t sleep on your local library https://t.co/heb4sD2hQY

    1.8K6210658K 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 106 interactions against 264K followers, an engagement rate of 0.04%. Measured over 9 original posts, its engagement rate beats 43% 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 9.4K times each, and 1.13% of those impressions turn into an interaction. That is about 3.55% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.33 posts a day over the last 30 days, though only 23% of days saw any activity at all. Most posts go out around 21:00 UTC, and Thursday is the busiest day of the week. Of the 9 posts sampled, 78% carry an image or video. The account's strongest tracked post pulled 56K interactions, about 188x its own typical post.

What is The Cinegogue's engagement rate on X?
The Cinegogue (@TheCinegogue) has an engagement rate of 0.04%, based on the median interactions across 9 original posts from the last 30 days against 264,283 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.04%, The Cinegogue 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 @TheCinegogue have real engagement?
Its engagement rate beats 43% 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 @TheCinegogue post?
Most posts go out around 21:00 UTC, and Thursday is its busiest day, at roughly 0.33 posts per day across the measured window.

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