文章基本信息

标题：Deciphering Bitcoin Blockchain Data by Cohort Analysis
本地全文：下载
作者：Yulin Liu ; Luyao Zhang ; Yinhong Zhao 等
期刊名称：Scientific Data
电子版ISSN：2052-4463
出版年度：2022
卷号：9
期号：1
页码：1-7
DOI：10.1038/s41597-022-01254-0
语种：English
出版社：Nature Publishing Group
摘要：Bitcoin is a peer-to-peer electronic payment system that has rapidly grown in popularity in recent years. Usually, the complete history of Bitcoin blockchain data must be queried to acquire variables with economic meaning . This task has recently become increasingly difcult, as there are over 1.6 billion historical transactions on the Bitcoin blockchain . It is thus important to query Bitcoin transaction data in a way that is more efcient and provides economic insights . We apply cohort analysis that interprets Bitcoin blockchain data using methods developed for population data in the social sciences . Specifcally, we query and process the Bitcoin transaction input and output data within each daily cohort . This enables us to create datasets and visualizations for some key Bitcoin transaction indicators, including the daily lifespan distributions of spent transaction output (STXO) and the daily age distributions of the cumulative unspent transaction output (UTXO) . We provide a computationally feasible approach for characterizing Bitcoin transactions that paves the way for future economic studies of Bitcoin .