Deep Learning-Based Community Detection Approach on Bitcoin Network

【Author】 Essaid, Meryam; Ju, Hongteak

【Source】SYSTEMS

【影响因子】2.895

【Abstract】Community detection is essential in P2P network analysis as it helps identify connectivity structure, undesired centralization, and influential nodes. Existing methods primarily utilize topological data and neglect the rich content data. This paper proposes a technique combining topological and content data to detect communities inside the Bitcoin network using a deep feature representation algorithm and Deep Feedforward Autoencoders. Our results show that the Bitcoin network has a higher clustering coefficient, assortativity coefficient, and community structure than expected from a random P2P network. In the Bitcoin network, nodes prefer to connect to other nodes that share the same characteristics.

【Keywords】bitcoin; network topology; community detection; deep learning; deep autoencoders

【发表时间】2022 DEC

【收录时间】2023-01-18

【文献类型】实验仿真

【主题类别】

区块链治理-技术治理-交易网络分析