Community Detection in Blockchain Social Networks

In this work, we consider community detection in blockchain networks. We specifically take the Bitcoin network and Ethereum as two examples, where serves different ways. For network, modify traditional method apply it to transaction social cluster users with similar characteristics. on other hand, define a bipartite graph based smart contract transactions. A novel algorithm which is designed for low-rank signals can help find users' communities user-token subscription. Based these results, strategies are devised deliver on-chain advertisements those same community. implement proposed algorithms real data. By adopting modified clustering algorithm, results basically consistent ground-truth of betting site has been announced public. Meanwhile, run strategy data, visualize an advertisement delivery Ropsten test net.