I’ve noticed that there are a few communities that tend to dominate when viewing all. Some days it gets to where looking at all isn’t very different than just looking at [email protected] or [email protected].
Before someone says “you can just block communities you don’t want to see,” it’s not that I never want to see them, it’s that I want to be able to have a view that shows me what is new and popular in a wide variety of communities. I appreciate seeing a few good memes in my feed. The problem is when that’s all I see. Changing the sort from active to hot or top x days doesn’t have much effect on which communities dominate, so that isn’t the solution either.
“You can just subscribe to communities you like”. True, but that has the effect of narrowing what I see. I’d like a view that showed me new things I never thought to subscribe to.
Lemmy devs - if you are reading this - it would be nice to have a feed that limited the number of posts showing up from any particular community. It could be a simple cutoff of 2 or 3 posts, or maybe some sort of weighting function to cause additional posts from the same community to appear lower in the sort order for that feed.
I’d love to hear what devs and other users think about this.
Edit: To everyone saying “just sort be new” - yes, that has its uses, but it only solves part of the problem. I’d like a feed that shows me what is new and popular, but from more than just one or two communities.
What’s liked by the general population is a good metric for providing general stuff to the general population and that’s what we’re talking about in All.
That average can however deviate a lot from the sweet spot for some people, quite possibly a large minority (even the majority depending on how concentrated or not people’s tastes are around it).
Something that looks at your previous choices (or even generally stated choices in the form of communities you subscribe to or block) similarly to what some search engines and some social media sites will do, can shift that toward more your own specific tastes, but that’s computationally more expensive and requires more users and more user data to get better results (basically it’s finding certain kinds of users and local minima which are more satisfactory to them).
I suspect something like an AI solution (not LLM, just a much simpler neural network) running on your own device that tries to predict what you’re going to click on and learns with what you do (or not) is the only way for a personalized “no fluff on my feed” solution, but that’s for apps running on top of Lemmy, not the Lemmy engine.