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Maybe a good time to revive some old collaborative filtering ideas I've had?
https://github.com/stackernews/stacker.news/discussions/2648
These methods allow you to construct similarity scores between posters and and between items, and individually preference rank items by posters.
Doesn't solve the problem of people with no data behind them, but their rankings could be some social aggregate using people with more data.
I'd say that most distinctively trust is a belief, so it needs a starting point (iirc that's what we had - trust flows from central points.) Reputation, how I see it, is more factual and measurable. Its not based on a belief but on merit. You build and lose it over time, but its not hierarchical. So your reputation doesn't have to influence mine in our interactions.
I understand that that doesn't solve the Sybil problem on its own though. I think John had written something about that not too long ago, but that was localized signal instead of globalized - and inherently still based on trust because of a LinkedIn style "connection of connection" legitimization. I don't think that that is suitable for a globalized "commons" approach, because the bias starts where the trust starts.
So I'm thinking a matrix more than a tree?