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Thoughts and Theory
Creating a Community-Specific Reputation Score for Users of Web3 Platform Mirror.xyz
Using Graph Data Science to compute a reputation score (betweenness centrality) on Mirror user interactions across Twitter, Governance, and Ethereum transactions
This post was first published on ath.mirror.xyz, be sure to subscribe there and follow me on twitter to get my most up-to-date crypto and data science content. Later on, this methodology was used for the first $WRITE token airdrop which you can read about here.
In my previous post on digital identity, I mentioned that “the tokenization of these graph shards could take many forms and will likely be layered upon by proof tokens.” I believe that sharded graph identity approach requires coming up with a community-specific reputation score that measures how influential a certain person has been in expanding a specific network. While some reputation scores may be more set in terms of having to have done X or Y actions, this score captures a users reputation in the context of other users in a more fluid manner — acting like a signal rather than a badge.
Typically in Web2, users are “rewarded” by an algorithm which will highlight them based on the engagement and attention they bring to the platform. Thus, their reputation score is just the number of likes or followers they have — regardless of who those…