Following https://tarte.nuage-libre.fr/c/fediverse/p/194717/we-need-more-users I decided to explore data a little bit more. I’m not the biggest fan of growth-as-as-target so I wanted to see how much the people were participating in the discussion.
The data
I took the data from the API explorer in https://api.fediverse.observer/ with this query:
query {
monthlystats {
date_checked
softwarename
total_posts
total_users
total_comments
}
}
Then parsed the json with this https://jqlang.org/ filter:
jq '.data.monthlystats | map(select(.total_users > 0 and (.softwarename == "lemmy" or .softwarename == "mbin" or .softwarename == "kbin" or .softwarename == "piefed"))) | group_by(.date_checked) | map( {date_checked: .[0].date_checked, total_users: ([.[] | .total_users] | add), total_posts: ([.[] | .total_posts] | add), total_comments: ([.[] | .total_comments] | add)}) | map({date_checked, posts: .total_posts/.total_users, comments: .total_comments/.total_users}) | sort_by(.date_checked) | map([.date_checked, (.posts | tostring), (.comments | tostring)]) | .[] | @csv'
(As you see I filtered for the threadiverse. I also did the same with all software, I’ll put the graph for that in comments)
Then did a good old’ chart
What to think of it
I don’t know. Users’ activity is on the rise and I find it nice


Good discovery tools are essential on a federated platform. An important part of twitter, facebook, and reddit success is/was that that they were the place for their particular style of content. You had a pretty good chance of being able to discover your old high school friends, because they were on the one platform. Then the (early) algorithm started discovering for you all the obscure content similar to your history.
Discovery has to work differently in a federated system. You can search for communities on Lemmy, but if your instance doesn’t already have someone subscribed to a community, then you’re not going to find it.