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.
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.
I did take Algorithms.
The definition we learned (let me know if I am wrong) is that an algorithm is a concrete set of steps to accomplish some goal in a finite amount of time given legitimate inputs.
Although in practice we use this more for stuff with a math formula and/or stuff you code. “Given the input of the world, if your eyes see it is raining outside, grab the umbrella from your closet. If you don’t see the umbrella, search for it. If the search takes 5+ minutes, just go to your destination” is an algorithm for trying to not get rained on, but in practice nobody’s going to be using that word that way.
I think the definition used online today is “some computer code that I can’t reliably determine the input/output of, that is used to my/society’s disadvantage in an exploitative way.”
Words evolve, and the word you learn in academia sometimes also gets used in real life and its usage changes in real life from what you would use in academia. And sometimes academia keeps using it that way, and real life keeps using it their different way, and so you use the same word while talking about slightly different concepts. And sometimes people in real life use it the academic way, others don’t, making things even more confusing… you just have to be aware people are using the same word to talk about two different things (or in this case, one group uses the word to talk about an unpleasant subset of the thing the other group uses the word to talk about) and clear up that misunderstanding.