Either the people in !steamdeck@lemmy.world are pretty horny or its an artifact of the dimensionality reduction and means nothing.
Edit: Actually it could also be that it just didn't collect enough data on that community and the most recent person was also active in nsfw communities. I was only able to get back 14ish days in the data for lemmy.world. They produce way to many comments and I got kicked out early.
Yeah pretty much. I wanted to see communities that had similar people that commented because I thought that would be a good way to see if there were similar kinds of discussions were happening in those communities.
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.
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.)
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.
How does it make the decision to recommend one post over another using the data it collects? Also does it treat all that data differently when ranking posts?
Either the people in !steamdeck@lemmy.world are pretty horny or its an artifact of the dimensionality reduction and means nothing.
Edit: Actually it could also be that it just didn't collect enough data on that community and the most recent person was also active in nsfw communities. I was only able to get back 14ish days in the data for lemmy.world. They produce way to many comments and I got kicked out early.
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