Bitcoin's Crypto Flow Network
This study provides a foundational analysis of Bitcoin's flow network for researchers and analysts interested in cryptoasset dynamics, though it is incremental in applying existing network methods to new data.
The researchers tackled the problem of understanding how Bitcoin flows among users by analyzing blockchain data from 2009 to 2020, constructing monthly networks of big players, and applying methods like bow-tie structure and Hodge decomposition to locate users in the flow; they found that the structure and hidden principal components are stable among these players.
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.