A Review on Data Analysis of Bitcoin Transaction Entity

Bitcoin is a decentralized cryptocurrency that has led to a new trading model. It allows people to trade directly without going through financial institutions such as banks. This model results in many transactions that occur outside the law and beyond ethical constraints. In such an anonymous environment, the large number of entities using Bitcoin, and the huge scale of the Bitcoin trading network make it difficult for users to have a rough idea of the entire trading network before transaction. Thus, it is of great theoretical and practical significance to summarize the research problems, achievements and possible research trends based on Bitcoin data analysis. Therefore, in this paper we review the literatures about data analysis on Bitcoin transaction entities. Starting from the relevant conceptual framework of Bitcoin, this paper divides the existing research models into three categories, heuristic algorithm identification of entities, transaction descriptive statistics and network analysis, and visual system analysis. By analyzing the transaction entity, Bitcoin transaction data can be processed in a manner which is similar to an account, such as a bank or credit card, thereby achieving the purpose of in-depth analysis of all transaction activities related to the account entity. Finally, we summarize the data analysis results of Bitcoin transaction network and prospects of the future research directions.