Oddbean new post about login | logout Here’s where Option 2 is headed. Suppose you have a normie friend you’ve been trying to recruit to nostr, who loves comic books and posts great summaries of his latest comic book finds. Normally he would make a nostr profile, look around, get no followers, see everyone talking bitcoin 24/7, get bored and leave. But you would create a superfollow for him in the category of Comic Books. The next day, your friend would have 10 new followers who all love comic books and saw your friend with one of the highest scores around in that category. And he’d stick around!
Yeah man absolutely we need to keep iterating and finding some usable middle ground. Anything with slight more signal than follows is a win. Option 1: would this be using kind 7 likes/dislikes? If so, trust would be derived from the interpretation of those events rather than being explicit, did I get that right? Regarding NIP-54 how likely is it that she adds the category? Option 2: love where it's headed, we need this. Communities fixes it too right? Today, how would we add a a mute event *in some context*? (reuse kind 10000 or does it have to be NIP-77?) In zap.store eventually I want to start asking, after a few app updates: "do you trust this dev" and make the user sign that attestation.
Probably yes about using kind 7 likes / dislikes. And a big fat yes to interpretation. I am increasingly thinking of NIP-77 as an idealization, with interpretation of proxy data into the idealized NIP-77 format as being a fundamentally important thing. Interpretation is done by the consumer, not the author of the primary data. It’s not far from what we do in real life! Maybe around half of NIP-54 articles are given a category, something like that. Eventually you’ll be able to invent new contexts and categories without the need for a wiki author to publish one, but gotta start somewhere. For a mute event in some context, I’m thinking I’d use NIP-77. But the beauty of interpretation is that if client A uses NIP-77 and client B uses an augmented kind 10000, the consumer can take data from both formats, interpret them into a common format, and pool them to create a larger dataset.