No matter which sort you use (except for new), content is recommended to you by activity. Depending on the sort (active, hot, top) it uses a slightly different mixture of votes/comments/time since post to determine the order.

The only exception is scaled, which boosts a little bit midsized communities, but still doesn’t manage to improve visibility of niche ones.

If lemmy is to truly start having active hobbyist communities instead of being 95% lefty US politics, Shitposts, and some tech stuff, it needs a sort that takes into account the user’s engagement.

For example, if I upvote / comment often in a community, there should be an option to have posts from the community be boosted in my feed, even if it’s a tiny community.

Let’s say I’m subscribed to !world@lemmy.world and !news@lemmy.world because I want to occasionally see news. However, I’m also subscribed to a couple hundred other communities, some of them who don’t manage to get more than a couple upvotes on their biggest posts. And whenever I see them I’m replying/upvoting because I’m passionate about that topic.

My feed shouldn’t be 95% c/news and c/world because those are the most upvoted and commented. I shouldn’t have to scroll down hundreds of posts to find “big” posts in small communities I interact with at any opportunity I get.

That’s why I think it would be beneficial to lemmy if the sort/algorithm took into account your engagement in a way.

It doesn’t have to be complicated, you can have a single number “engagement score” for every community calculated with a basic formula, and that number is used as a boost to the community.

I’m aware that there are some examples of successful niche communities on lemmy. But that’s mainly because either a significant chunk of the lemmy userbase is into that niche (let’s face it the lemmy community is not a representative sample of the world population, we tend to be very similar people), or because the posts on it are simplified image/video type posts which appeal to people who don’t know much about the subject.

  • LainTrain@lemmy.dbzer0.comEnglish
    1·
    10 hours ago

    It’s arbitrary but something like SELECT * FROM posts WHERE datePosted < ( currentDay() - 7) ORDER BY upvotes; doesn’t feel like an algorithm as it is now used in common parlance to me.

    A simple quantitative analysis of an existing metric and (upvotes in the above super simplified example) is just not really the same thing in practice as say: multiple linear regression of hidden backend engagement metrics gathered through things like cursor movements to pick a suggested video that is predicted to optimize the best for watch time and CTR from a list of videos on a balance of personalized and generalized (through tracking trends amongst demographics) favourites topics and other qualities classified and categorised by a whole other black box involving all sorts of classifier models from text to images and so on.

    Idk, I didn’t take algorithms in CS at uni, so this is just a layman’s two cents. I’m happy to be explained to why this isn’t a valid perspective.