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?
There’s honestly nothing wrong with any of those options including 2. I get people see algorithm and recommendation and have aneurisms but this space isn’t looking to harm anyone intentionally. If there’s any space we should trust with any kind of algorithms it’s this space as there’s not the same incentives that Big Social has. As long as users can consent and have control.
But to answer your question it would take some hybrid search on top of an aggregator that is explicitly public and respects people’s flags. I know Mastodon is working on a discover service