this post was submitted on 11 May 2026
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MAU vs UE (piefed.social)
submitted 1 month ago* (last edited 1 month ago) by ozoned@piefed.social to c/fediverse@lemmy.world
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I know lots of folks are talking about Monthly Active Users when it comes to health of the Fediverse.

We use that to compare social medias and even ourselves, a social network, to each other.

I argue we should be focused on user engagement. I know LinkedIn has "impressions", but idk what that means.

So I wonder if there's a good way to generate this. Someone posting is the highest, commenting, subscribing, liking, disliking, and follow on down. I guess that would be a statistical model? But with diminishing returns. One SUPER ACTIVE ANNOYING poster does not a network make, but "media" it does.

I don't have a clue how this would work statistically. But I theorize, that while we're smaller MAU, our user engagement is significantly higher when population size is accounted for.

Is there any data anyone knows of to back this up or disapprove it? I'm pro small.social though, so maybe I'm wrong. Any data scientists in the Fediverse? :-D

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[โ€“] Auster@thebrainbin.org 14 points 1 month ago (1 children)

MAU afaik is the easier number to find closer to actual engagement.

But I think engagement could be measured by (comments + votes + downvotes + boosts if available) / (number of posts).

However, size of a given instance, specially for smaller ones, may cause odd fluctuations, so standard deviation or a threshold of small/medium/large instances may be needed when ranking.

Also an instance that had a massive initial engagement metric, or an abysmal one, would have its overall score affected for quite a while, affecting the interpretation of others about its metrics. So to mitigate, maybe taking the numbers by time period may be better, e.g. one ranking for the past week, one for the month, one for the semester, one for the year, and one for all time.

[โ€“] hendrik@palaver.p3x.de 3 points 1 month ago* (last edited 1 month ago)

If my quickly written down SQL query is right, those are the numbers for the last month from my instance's perspective (my subscribed communities):

 num_comments | upvotes_on_posts | downvotes_on_posts | num_posts 
--------------+------------------+--------------------+-----------  
       188597 |          1646685 |              46461 |     13928

So without the boosts, it'd be a total score of 135.