Characterizing key agents in the cryptocurrency economy through blockchain transaction analysis
Web Mining Laboratory, Department of Media and Communication, City University of Hong Kong, 18 Tat Hong Avenue, Kowloon, Hong Kong SAR, China
2 School of Computer Science and Engineering, Southeast University, 2 Dongnandaxue Road, 211189, Nanjing, China
Accepted: 21 April 2021
Published online: 1 May 2021
The cryptocurrency economy provides a comprehensive digital trace of human economic behavior: almost all cryptocurrency users’ activities are faithfully recorded in transactions on public blockchains. However, the user identifiers in the transaction records, i.e., blockchain addresses, are anonymous. That is, they cannot be associated with any real “off-chain” identify of actual users. Nonetheless, identifying the economic roles of the addresses from their past behaviors is still feasible. This paper analyzes Ethereum token transactions, characterizes key economic agents’ behavior from their transaction patterns, and explores their identifiability through interpretable machine learning models. Specifically, six types of most active economic agents are considered, including centralized cryptocurrency exchanges, decentralized exchanges, cryptocurrency wallets, token issuers, airdrop services, and gaming services. Transaction patterns such as trading volume, transaction tempo, and structural properties of transaction networks are defined for individual blockchain addresses. The results showed that cryptocurrency exchanges and online wallets have signature behavior patterns and hence can be accurately distinguished from other agents. Token issuers, airdrop services, and gaming services can sometimes be confused. Moreover, transaction networks’ features provide the richest information in the economic agent’s identification.
Key words: Cryptocurrency / Ethereum / Deanonymization / Network analysis / Machine learning
© The Author(s) 2021
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.