Do the rich get richer? An empirical analysis of the BitCoin transaction network

TL;DR

This paper analyzes the complete Bitcoin transaction network to understand its growth, structure, and wealth distribution dynamics, revealing preferential attachment mechanisms and a scaling relation between node degree and wealth.

Contribution

It provides the first detailed empirical analysis of the Bitcoin transaction network, uncovering the mechanisms driving its growth and wealth distribution.

Findings

Network growth driven by linear preferential attachment

Wealth distribution governed by sublinear preferential attachment

Identified a scaling relation between node degree and wealth

Abstract

The possibility to analyze everyday monetary transactions is limited by the scarcity of available data, as this kind of information is usually considered highly sensitive. Present econophysics models are usually employed on presumed random networks of interacting agents, and only macroscopic properties (e.g. the resulting wealth distribution) are compared to real-world data. In this paper, we analyze BitCoin, which is a novel digital currency system, where the complete list of transactions is publicly available. Using this dataset, we reconstruct the network of transactions, and extract the time and amount of each payment. We analyze the structure of the transaction network by measuring network characteristics over time, such as the degree distribution, degree correlations and clustering. We find that linear preferential attachment drives the growth of the network. We also study the dynamics taking place on the transaction network, i.e. the flow of money. We measure temporal patterns and the wealth accumulation. Investigating the microscopic statistics of money movement, we find that sublinear preferential attachment governs the evolution of the wealth distribution. We report a scaling relation between the degree and wealth associated to individual nodes.