Portrait of decentralized application users: an overview based on large-scale Ethereum data

This paper attempts to profile DApp users through publicly available data and applies an unsupervised clustering method on the 230,000 addresses to distinguish investors and players and analyze their behavioral patterns and sensitivity to blockchain markets, such as ETH prices.