I think this is a great idea. And I have a solution to the bootstrap problem.

The solution is: interpretation of proxy data “as if” it were NIP-77 formatted data. For example, if you “like” a wikifreedia article filed under Category X, my software interprets that “as if” you issued a NIP-77 attestation, to that author, in the context of X. But since like != trust (well, maybe it does and maybe it doesn’t, I have no way of knowing), I “interpret” a really low confidence, like maybe 1% or 5%. That way, we start out with a sea of NIP-77-formatted trust data. And you’ll know that if you REALLY trust someone in some context, like if I REALLY trust nostr:npub1a2cww4kn9wqte4ry70vyfwqyqvpswksna27rtxd8vty6c74era8sdcw83a to write wikifreedia articles on economics, and if I want my app to give an added boost to her other content and I’m OK with saying this publicly, then I’m gonna have to issue an actual NIP-77 attestation and set the confidence to something more meaningful than 1% or 5%. In this way, the pool of high quality contextual trust attestations can accumulate gradually.

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If Alice “follows” Bob in nostr, we interpret that “as if” she had issued a trust attestation of Bob, score: 100, confidence: 5%, context: to curate content on nostr.

Our next step is to replace WoT scores with “influence” scores. Two salient features of influence score for this discussion: they are contextual, and they have to take the confidence variable into account.

Yes, I can bootstrap trust data from zero by using follows, but the more difficult part is to bootstrap the content itself, e.g. make people to post lots of interesting articles and discussion starters and come back regularly. Like it happened in reddit. I still like the simplicity of the idea.

Is there anyone doing anything like what you envision?

Seems like no. There were uncommitted trials doing that.

What about curating content that already exists? So that you would not need to build a pile of content from scratch, ie. no need to build Reddit from scratch. (Not that it isn’t a cool idea in and of itself.)

There are lots of different types of content on nostr. So one question to consider: which category of content would be the lowest hanging fruit for decentralized curation? Right now I’m working on wiki articles, but there are so many other juicy targets.

Some may be more amenable than others. Stratification of a nostr feed is typically chronological, and it’s not immediately obvious how to combine age + WoT score to reorder the nostr feed. For a wiki topic, I think it’s more obvious: just order them best to worst.

Certain lists like products for sale, movies, music, etc certainly would benefit directly from curation by WoT.