Deciphering Bitcoin Blockchain Data by Cohort Analysis

TL;DR

This paper introduces a cohort analysis method for Bitcoin blockchain data, enabling efficient querying and economic insights from over 1.6 billion transactions by analyzing transaction age and lifespan distributions.

Contribution

It applies social science cohort analysis techniques to Bitcoin data, providing a novel, computationally feasible approach for economic interpretation of blockchain transactions.

Findings

Created datasets and visualizations of transaction age distributions

Enabled efficient analysis of large-scale Bitcoin transaction data

Facilitated future economic studies of Bitcoin blockchain

Abstract

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 difficult, 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 efficient and provides economic insights. We apply cohort analysis that interprets Bitcoin blockchain data using methods developed for population data in the social sciences. Specifically, 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.