Decoding Decentralized Finance Transactions through Ego Network Motif Mining

TL;DR

This paper introduces a method to analyze DeFi transactions by extracting ego network motifs from token transfer networks, enabling identification of smart contract functions and user activities despite data challenges.

Contribution

It proposes a novel motif mining approach to decode DeFi transactions, improving understanding of user and contract interactions in decentralized finance.

Findings

Efficient identification of smart contract methods using network motifs

Insights into user and contract activity patterns in DeFi

Robust analysis despite incomplete or inaccurate data

Abstract

Decentralized Finance (DeFi) is increasingly studied and adopted for its potential to provide accessible and transparent financial services. Analyzing how investors use DeFi is important for reaching a better understanding of their usage and for regulation purposes. However, analyzing DeFi transactions is challenging due to often incomplete or inaccurate labeled data. This paper presents a method to extract ego network motifs from the token transfer network, capturing the transfer of tokens between users and smart contracts. Our results demonstrate that smart contract methods performing specific DeFi operations can be efficiently identified by analyzing these motifs while providing insights into account activities.