I didn't measure activity for this map. Each dot represents a community. I only used the communities that were on the top 35 instances (except lemmings.world which it couldn't grab any comments for.)
Well I used dimensionality reduction to make it 2D so the axes are how the algorithm chose to compress it.
The original data had each data point as a community and the features as a frequency of a user posting in that community.
There is actually already a website where people just recreated the bee movie by hand so idk it might actually work as a legal argument.
A few but none that were as good at collecting up to date episodes.
I know I was talking about how the map I linked to worked which is based on reddit.
People say they have problems with discoverability. A map will help people find the content they want faster.
The map up above checks how similar two subreddits are by checking how much overlap the people that comment in both communities there is. It could be the same as that or maybe something different.
The easiest would be to have countries similar to how it had in the map of reddit be the instances and show the connections between subscribers maybe.
I never said we shouldn't use algorithms I just think what those algorithms were doing could be different.
Maybe, I'm not sure because I don't really have much knowledge on self-hosting. I did find this on their website though so you could start here:
For example most of the red dots to the top right are nsfw communities and it was able to clump like that because the people that comment in those communities tend to comment in the other nsfw communities as well.
edit: left -> right
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