Temporal and Geographical Analysis of Real Economic Activities in the Bitcoin Blockchain
This work addresses centralization issues in Bitcoin for blockchain researchers and users, though it is incremental as it builds on existing classification methods.
The paper tackled the problem of analyzing real economic activity in the Bitcoin blockchain by focusing on retail user transactions, revealing that most payments involve a small group of Frequent Receivers, raising centralization concerns, and quantifying biases in a dataset for actor identification.
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.