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Data-driven analysis of Bitcoin properties: exploiting the users graph

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Abstract

Data analytic has recently enabled the uncovering of interesting properties of several complex networks. Among these, it is worth considering the bitcoin blockchain, because of its peculiar characteristic of reflecting a niche, but also a real economy whose transactions are publicly available. In this paper, we present the analyses we have performed on the users graph inferred from the bitcoin blockchain, dumped in December 2015, so after the occurrence of the exponential explosion in the number of transactions. We first present the analysis assessing classical graph properties like densification, distance analysis, degree distribution, clustering coefficient and several centrality measures. Then, we analyse properties strictly tied to the nature of bitcoin, like rich-get-richer property, which measures the concentration of richness in the network.

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Acknowledgements

The authors would like to thank Dr. Christian Decker and Prof. Roger Wattenhofer of the Distributed Computing Group, ETH Zurich for providing us the blockchain in Protocol Buffers format. This work was supported by PRA, Progetto di Ricerca di Ateneo, “Big Data, Social Mining and Risk Management”, University of Pisa.

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  1. Department of Computer Science, University of Pisa, Pisa, Italy

    Damiano Di Francesco Maesa, Andrea Marino & Laura Ricci

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  1. Damiano Di Francesco Maesa
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  2. Andrea Marino
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  3. Laura Ricci
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Correspondence to Damiano Di Francesco Maesa.

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Di Francesco Maesa, D., Marino, A. & Ricci, L. Data-driven analysis of Bitcoin properties: exploiting the users graph. Int J Data Sci Anal 6, 63–80 (2018). https://doi.org/10.1007/s41060-017-0074-x

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