Identification of a Set of Influential Nodes in Social Networks Based on Voting Mechanism
[Objective]This paper aims to achieve a trade-off between running efficiency and accuracy,this paper proposes a voting-based algorithm for identifying a set of influential nodes in social networks named KSEVoteRank.[Methods]Considering the node importance and the neighborhood information,the voting ability of a node is defined and a voting allocation strategy is designed.Meanwhile,an attenuation factor is introduced to discount the voting ability of neighbors.Finally,the node with the highest voting score is iteratively selected as the seed node.[Results]The experimental results show that the influence overlap of a set of influential nodes detected by the KSEVoteRank algorithm in the large social network Ca-AstroPh dataset is about 21％less than that of the VoteRank algorithm.[Limitations]During the repeated voting process,the voting allocation strategy of the neighbors is fixed,which may cause a slight deviation in the theoretical results.[Conclusions]The KSEVoteRank algorithm,based on a voting mechanism,selects a set of influential nodes in a distributed manner to achieve a widespread propagation of influence,which is applicable to large social networks.
Social NetworkInfluence MaximizationVoting MechanismAttenuation Factor
万方数据
维普
