Bitcoin's Crypto Flow Network

TL;DR

This paper analyzes Bitcoin's global crypto flow network by constructing monthly user networks, applying structural and probabilistic models, and revealing stable core and flow components over time.

Contribution

It introduces a comprehensive network analysis of Bitcoin transactions using bow-tie structure, Hodge decomposition, and non-negative matrix factorization, revealing stable flow patterns among major users.

Findings

Stable bow-tie structure among big players

Identification of principal flow components

Model equivalence to probabilistic latent semantic analysis

Abstract

How crypto flows among Bitcoin users is an important question for understanding the structure and dynamics of the cryptoasset at a global scale. We compiled all the blockchain data of Bitcoin from its genesis to the year 2020, identified users from anonymous addresses of wallets, and constructed monthly snapshots of networks by focusing on regular users as big players. We apply the methods of bow-tie structure and Hodge decomposition in order to locate the users in the upstream, downstream, and core of the entire crypto flow. Additionally, we reveal principal components hidden in the flow by using non-negative matrix factorization, which we interpret as a probabilistic model. We show that the model is equivalent to a probabilistic latent semantic analysis in natural language processing, enabling us to estimate the number of such hidden components. Moreover, we find that the bow-tie structure and the principal components are quite stable among those big players. This study can be a solid basis on which one can further investigate the temporal change of crypto flow, entry and exit of big players, and so forth.