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.

加密货币经济提供了人类经济行为的全面数字跟踪：几乎所有加密货币用户的活动都忠实地记录在公共区块链上的交易中。但是，交易记录中的用户标识符（即区块链地址）是匿名的。也就是说，它们不能与实际用户的任何真实“链外”标识相关联。尽管如此，从地址过去的行为中确定地址的经济作用仍然是可行的。本文分析了以太坊代币交易，从关键经济主体的交易模式表征其行为，并通过可解释的机器学习模型探索其可识别性。具体来说，考虑了六种最活跃的经济主体，包括集中式加密货币交易所，去中心化交易所，加密货币钱包，令牌发行者，空投服务和游戏服务。为单个区块链地址定义了诸如交易量，交易节奏和交易网络的结构属性之类的交易模式。结果表明，加密货币交易所和在线钱包具有签名行为模式，因此可以与其他代理准确地区分开。有时可能会混淆令牌发行者，空投服务和游戏服务。此外，交易网络的功能在经济主体的识别中提供了最丰富的信息。结果表明，加密货币交易所和在线钱包具有签名行为模式，因此可以与其他代理准确地区分开。有时可能会混淆令牌发行者，空投服务和游戏服务。此外，交易网络的功能在经济主体的识别中提供了最丰富的信息。结果表明，加密货币交易所和在线钱包具有签名行为模式，因此可以与其他代理准确地区分开。有时可能会混淆令牌发行者，空投服务和游戏服务。此外，交易网络的功能在经济主体的识别中提供了最丰富的信息。