Hey nostr:npub1zteqcekncmnt07d3zulsayd4m4ppm3nh6m3upm9sasljy89h2efqzcwcyy, great article.

First, I am all for using spontaneous user interactions as input for discovery algorithms, as opposed to NIP77 where the user is asked for a trust judgment that will likely require bootstrapping a new type of user interaction.

Second, I like zaps because they carry a value signal (assuming the sender is not colluding with the recipient).

I think your proposed algorithm is part of a more general class of algorithms that I've described in my
Navigating the Social Graph https://pippellia.com/pippellia/Social+Graph/Navigating+the+social+graph

Here is how I see it:

- The input is some social graph whose edges represent some form of social relationship, such as who follows who, or, as in your case, who zapped who and how much.

- some propagation rule is applied (in your case, it's direct propagation)

- calculate a certain set of candidates

- apply a sorting rule to sort the candidates (this can be pagerank, local pagerank, trustrank, zap weight...)