Bitcoin's Crypto Flow Network

Yoshiyuki Fujiwara, Rubaiyat Islam
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引用次数: 2

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.
比特币的加密流网络
加密货币如何在比特币用户之间流动是理解全球范围内加密资产结构和动态的一个重要问题。我们收集了比特币从诞生到2020年的所有区块链数据,从钱包的匿名地址中识别用户,并通过将普通用户作为大玩家来构建每月的网络快照。我们运用蝴蝶结结构和霍奇分解的方法来定位用户在整个加密流的上游、下游和核心。此外,我们通过使用非负矩阵分解来揭示隐藏在流中的主成分,我们将其解释为概率模型。我们表明,该模型相当于自然语言处理中的概率潜在语义分析,使我们能够估计此类隐藏组件的数量。此外,我们发现,在这些大公司中,领结结构和主成分是相当稳定的。这项研究可以作为一个坚实的基础,在此基础上,人们可以进一步研究加密货币流动的时间变化、大型参与者的进入和退出等等。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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