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

PLoS One. 2014 Feb 5;9(2):e86197. doi: 10.1371/journal.pone.0086197. eCollection 2014.


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 some 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 law between the degree and wealth associated to individual nodes.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Databases, Genetic*
  • Models, Econometric*

Grants and funding

This work has been supported by the European Union under grant agreement No. FP7-ICT-255987-FOC-II Project. The authors thank the partial support of the European Union and the European Social Fund through project (grant no.: TAMOP-4.2.2.C-11/1/KONV-2012-0013), the OTKA 7779 and the NAP 2005/KCKHA005 grants. EITKIC_12-1-2012-0001 project was partially supported by the Hungarian Government, managed by the National Development Agency, and financed by the Research and Technology Innovation Fund and the MAKOG Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.