With the popularization of intelligent technology,high-quality community detection has become a hot topic in so-cial network research.Label propagation algorithm(LPA)has been widely attracted because of its linear time complexity and with-out predefining the objective function and community number.However,in label propagation,LPA is uncertainties and random-ness,which affects the group's accuracy and stability.Therefore,in this paper,a label propagation community detection approach based on peak density is proposed,called DPC-RWL.Firstly,the density peak clustering algorithm is employed to search the core node set of the community.Secondly,the weight between each node and the core set of nodes is calculated,and then the maximum value is selected as its weight.Eventually,the belonging degree function based on label propagation is utilized for propagation.The experiments between the real and LFR artificial benchmark networks show that the proposed algorithm can accurately and efficiently identify community structure.
density peak clusteringlabel propagationnode weighsocial networks
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