nostr:nprofile1qy88wumn8ghj7mn0wvhxcmmv9uq3zamnwvaz7tmwdaehgu3wwa5kuef0qqszv6q4uryjzr06xfxxew34wwc5hmjfmfpqn229d72gfegsdn2q3fgfjtyk0 and nostr:nprofile1qyvhwumn8ghj76rzwghxxmmjv93kcefwwdhkx6tpdshszrnhwden5te0dehhxtnvdakz7qpqjlrs53pkdfjnts29kveljul2sm0actt6n8dxrrzqcersttvcuv3qy09qsr, the WoT coracle has a few issues, that will become more and more apparent as nostr grows:
1. each follows/mute count 1. This doesn't consider that there are people that follow 5k others, while most are more picky, nor considers the reputation of the one following. These nuances are reflected by the pagerank formula for instance https://en.wikipedia.org/wiki/PageRank.
The contribute of one's follows are proportional to its pagerank and inversely proportional to the size of the follow-list. This is true both for global or personalized pagerank.
2. a users has only information on the two-hop network around him. This consists of an average of ~50k people, which is fine for now because the network is small, but won't scale when nostr is at 10M+ users.
Vertex abstracts away all of these complexities, and gives simple to use end-points for many common operations like:
- sorting replies, comments, zaps...
- verify reputation of a target npub
- get recommendations
I am more than happy to have a chat about how give access to these tools guys, just let me know
nostr:npub1ye5ptcxfyyxl5vjvdjar2ua3f0hynkjzpx552mu5snj3qmx5pzjscpknpr just convinced to stop using the Follow concept entirely, lol.
Very curious how pageranking will be done in a more Community centered layer of Nostr, with atomic Label/Badge events.
honestly if a community is small enough, Pagerank is not needed because all npubs have been invited.
For open communities, then Pagerank is useful for helping the moderator know which one to kick out automatically
That's true **within** a community.
The questions come when you want to use the Communitues someone is active on as data to derive a notion of **his network** from.
As in:
When he browse to the page of a product / a new community / a podcast show / ....
Do you show the profiles on his network that are part of his network that use that product, are active in that community and are listening to that podcast?
If yes, then you need a way to define that network.
Or for the main Vertex use case too:
For knowing if you are the real Pip, you are now looking at the Web of Follows.
What changes mathematically when we start looking at a Web of Communities?
A web that works with:
- Badges: awarded by Communities, (optionally also accepted by profiles)
- payments (pay to poast, pay for badge, zap the communikey, ....)
- atomic events for reporting and black "listing"
It really depends on the usecase, there is no silver bullet.
For example, if you are looking at a product, you could fetch all reviews for that product, and drop reviews from npubs whose pagerank is lower than a threshold. Or you could weight that review using the pagerank (influencers have higher influence, not necessarily a good idea).
Or maybe you can show the average vote of the members of the community, which is more contained. All tradeoffs.
Pagerank can be run on any graph, so one could built it by looking at who replied/zapped/liked to whom, in a given setting.
Also, not all signal should be condensed into a single rank, multiple trust signals should be provided imo. Number of followers, ranks, nip05, badges, all give some clues that your brain can interpret.
