Related Experiment Video
Updated: Sep 27, 2025

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
Published on: December 10, 2012
Deciphering Bitcoin Blockchain Data by Cohort Analysis
Yulin Liu1,2, Luyao Zhang3,4, Yinhong Zhao1,5
1SciEcon CIC, London, WC2H 9JQ, United Kingdom.
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.
Related Concept Videos
Cross-Sectional Research
Interpreting Run Charts
Statistical Methods for Analyzing Epidemiological Data
Longitudinal Studies
Analysis of Population Pharmacokinetic Data
Ogive Graph

