A place for developers to talk about building on Farcaster.

/dev

small mvp of the @balajis.eth follow graph idea

@nobuilder.eth took the following data of the top 20% users from a hub and we plugged it into vis.js

effect is very clustered for now, if you have ideas on how to visualize it please ping us on gh!

play with it here:

Author of The Network State.
Work with me: jobs.ns.com

Amusement, wonder, and uncertainty. now [redacted], prev @neynar ✴︎ libred.org

small mvp of the @balajis.eth follow graph idea

@rafi took the following data of the top 20% users from a hub and we plugged it into vis.js

effect is very clustered for now, if you have ideas on how to visualize it please ping us on gh!

play with it here: https://nobuilder.github.io/farcaster-social-graph/

Great work! Can you try partitioning the graph into dense subgraphs, like below? This would identify the Farcaster tribes.

There are various approximate algorithms for clique detection, dense subgraph identification, and factorization of a matrix into block diagonals that you might use.

this is great @woj.eth 
we’re working on a personalized people and cast recommendation for fc. 

Using eigentrust to rank profiles. edges and the weights in the graph can be configured.. using follows, likes, comments, recasts.

work in progress here

this is great @woj.eth 
we’re working on a personalized people and cast recommendation for fc. 

Using eigentrust to rank profiles. edges and the weights in the graph can be configured.. using follows, likes, comments, recasts.

work in progress here https://cast.k3l.io/