For any social network, not just a federated one.
My thoughts: The way it works in big tech social networks is like this:
- **The organic methods: **
- your followee shares something from a poster you don’t follow
- someone you don’t follow comments on a post from someone you follow
- you join a group or community and find others you currently don’t follow
- 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?
The problem I ran into is that every single platform that primarily interacted with Mastodon (The keys, etc.) had the same exact same set of problems.
While yes, my Firefish instance had search, what was it searching? Local data only, and once I figured out that Mastodon-style replies didn’t federate to all of someone’s followers, it became pretty clear that it was uh, not very useful.
You can search, but any given server may or may not have access to data you actually want and thus, well, you just plain cannot meaningfully search for shit unless you go to one of the mega instances, or join giant piles of relays and store gigabyte upon gigabyte upon gigabyte of garbage data you do not care about.
The whole implementation is kinda garbage for search-based discovery from it’s very basic design all the way through to everyone’s implementations.