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.

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Author Of this post: <a href="">Yoshi Fujiwara</a>, <a href="">Rubaiyat Islam</a>

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