The Spatiotemporal Scaling Laws of Bitcoin Transactions

TL;DR

This paper investigates the geographic and temporal patterns of Bitcoin transactions, revealing scaling laws and modeling these dynamics to understand user behavior and regional differences in the network.

Contribution

It empirically characterizes Bitcoin's spatiotemporal scaling laws and introduces a Markovian model to approximate its geographic transaction patterns.

Findings

Bitcoin exhibits significant geographic activity differences.

A Markovian model effectively captures Bitcoin's spatiotemporal patterns.

Geographical disparities have implications for regulation and decentralization.

Abstract

This study, to the best of our knowledge for the first time, delves into the spatiotemporal dynamics of Bitcoin transactions, shedding light on the scaling laws governing its geographic usage. Leveraging a dataset of IP addresses and Bitcoin addresses spanning from October 2013 to December 2013, we explore the geospatial patterns unique to Bitcoin. Motivated by the needs of cryptocurrency businesses, regulatory clarity, and network science inquiries, we make several contributions. Firstly, we empirically characterize Bitcoin transactions' spatiotemporal scaling laws, providing insights into its spending behaviours. Secondly, we introduce a Markovian model that effectively approximates Bitcoin's observed spatiotemporal patterns, revealing economic connections among user groups in the Bitcoin ecosystem. Our measurements and model shed light on the inhomogeneous structure of the network: although Bitcoin is designed to be decentralized, there are significant geographical differences in the distribution of user activity, which has consequences for all participants and possible (regulatory) control over the system.