Temporal and Geographical Analysis of Real Economic Activities in the Bitcoin Blockchain

TL;DR

This paper analyzes real economic activities in the Bitcoin blockchain, classifies users into categories, and examines weekly patterns and geographical biases to understand transaction dynamics and centralization concerns.

Contribution

Introduces a heuristic method to classify Bitcoin users and analyzes transaction patterns and geographical biases in real economic activities.

Findings

Most real transactions involve Frequent Receivers.

A small fraction of total value is exchanged with Frequent Receivers.

Identifies geographical biases in Bitcoin activity.

Abstract

We study the real economic activity in the Bitcoin blockchain that involves transactions from/to retail users rather than between organizations such as marketplaces, exchanges, or other services. We first introduce a heuristic method to classify Bitcoin players into three main categories: Frequent Receivers (FR), Neighbors of FR, and Others. We show that most real transactions involve Frequent Receivers, representing a small fraction of the total value exchanged according to the blockchain, but a significant fraction of all payments, raising concerns about the centralization of the Bitcoin ecosystem. We also conduct a weekly pattern analysis of activity, providing insights into the geographical location of Bitcoin users and allowing us to quantify the bias of a well-known dataset for actor identification.