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.
翻译:Bitcoin用户之间的加密流是如何在全球范围理解加密资产的结构和动态的一个重要问题。 我们汇编了从它起源到2020年的所有Bitcoin链条数据,识别了钱包匿名地址的用户,并通过关注普通用户作为大玩家而制作了网络月度简况。 我们采用了弓领结构和Hodge分解的方法,以便定位用户在上游、下游和整个加密流的核心。 此外,我们通过使用非负式矩阵系数化,发现了流动中隐藏的主要组成部分,我们把它解释为一种概率模型。我们显示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成部分的数量。此外,我们发现弓领结构和主要组成部分在这些大玩家中间相当稳定。这项研究可以作为一个坚实的基础,进一步调查大玩家的隐姓流、出和出的时间变化,等等。