identification of influential nodes in multilayernetworks using the concept of communityrepresentatives

Abstract—selection of seed nodes (influential nodes) in social networks is very important and necessary. because these nodes can infiltrate other nodes and bring dynamics and control of information dissemination in the network. the goal of influence maximization (im) is to select the minimum number of seed nodes to maximize the information diffusion or social impact. this issue is necessary for advertising, viral marketing, rumor control, etc. many studies have been done on the influence maximization problem in single layer or monoplex networks. in multiplex networks where the nodes in each layer may have different connections with other nodes, identifying seed nodes for influence maximization has a different nature, and the desired results with classical methods may not be obtained. in this article, a community-based influence maximization method in multiplex networks is proposed. the basis of the proposed method is to determine the representative seed for each community. the representative node is selected in a way that covers more communities. in the proposed method, first, multi-stage filtering is performed on the nodes inside each layer to remove leaf nodes and nodes with low degrees. then the communities inside each layer are identified with classical methods and the list of nodes of each community is maintained. after identifying the communities, the seed nodes for each community are selected according to the complete structure criteria of the layers of the multiplex network. the efficiency of the proposed method has been evaluated on real datasets and the obtained results show high accuracy in determining seed nodes.