The recommendation engine methods: content you do not follow shows up, and you are likely to engage in it based on statistical models. Big tech is pushing this more and more.
Search: you specifically attempt to find what you're looking for through some search capability. Big tech is pushing against this more and more.

In my opinion, the fediverse covers #1 well already. But #1 has a bubble effect. Your followees are less likely to share something very drastically different from what you already have.

The fediverse is principally opposed to #2, at least the way it is done in big tech. But maybe some variation of it could be done well.

#3 is a big weakness for fediverse. But I am curious how it would ideally manifest. Would it be full text search? Semantic search? Or something with more machine learning?

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[–] lizard-socks@pandacap.azurewebsites.net 2 points 14 hours ago (1 children)

On art sites - i.e. DeviantArt and the various furry sites that copied it in the 2010s (many of which are still very much active) - every user has a "favorites" page to which they can add anyone else's posts. This also sends a notification to the artist. When I get a favorite or a comment, I always check that artist's posts and their favorites page, to see what else they have favorited, and I can reliably find new people and posts that way. I don't think this is really analogous to a boost, since it doesn't show up in your feed, but it's also not quite the same as "likes", since it's much more expected that people will go looking through it (people don't really look at other people's likes much, even though they are almost always public). Plus it's almost guaranteed that it'll be filled with art, as opposed to blog or microblog style text posts, so you're not as subjected to the hot takes of random people you don't know.

[–] matcha_addict@lemy.lol 2 points 14 hours ago

It's sort of like creating your own hand-curated feed for other people to see