A pareto front-based metric to identify major bitcoin networks influencers

Abstract

Bitcoin is a novel digital currency that relies on cryptography instead of a central authority to verify transactions. Without a central authority, Bitcoin requires a complete list of all transactions to be made public so that they can be verified by all users. The major network influencers in a Bitcoin network are defined as users that accumulate a disproportionate amount of wealth compared to others. However, there are some defined metrics to identify major network influencers, considering multiple criteria can improve the detection task. In this paper, a multi-criteria metric is applied to identify the major network influencers based on the history of their activities recorded on the blockchain. The proposed metric is based on the Pareto front on multiple criteria, the maximum increase in wealth with the least amount of activity using non-dominated sorting inspired from multi-objective optimization. The provided descriptive statistics on extracted data demonstrates the efficiency of the proposed metric on identification of major influencers.