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.
pippellia / Pip the social graph guy
npub176…7vgup
2025-06-18 20:02:09
in reply to nevent1q…4kte
Author Public Key
npub176p7sup477k5738qhxx0hk2n0cty2k5je5uvalzvkvwmw4tltmeqw7vgupPublished at
2025-06-18 20:02:09Event JSON
{
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"pubkey": "f683e87035f7ad4f44e0b98cfbd9537e16455a92cd38cefc4cb31db7557f5ef2",
"created_at": 1750276929,
"kind": 1,
"tags": [
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],
[
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],
[
"r",
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],
[
"r",
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],
"content": "It really depends on the usecase, there is no silver bullet.\n\nFor 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).\n\nOr maybe you can show the average vote of the members of the community, which is more contained. All tradeoffs.\n\nPagerank can be run on any graph, so one could built it by looking at who replied/zapped/liked to whom, in a given setting.\n\nAlso, 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.",
"sig": "357a53304bea6a2db29b7e4a4dacd716ec89e3c741a97f2aee2030ad92bca049355b313abbabfbb14d2fc27be56d70511d712f5c652ceff37ec91c9c79390da0"
}