In this paper, we consider a novel game theory model for the competitive influence\nmaximization problem. We model this problem as a simultaneous non-cooperative game with\ncomplete information and rational players, where there are at least two players who are supposed\nto be out of the network and are trying to institutionalize their options in the social network;\nthat is, the objective of players is to maximize the spread of a desired opinion rather than the\nnumber of infected nodes. In the proposed model, we extend both the Linear Threshold model\nand the Independent Cascade model. We study an influence maximization model in which users�\nheterogeneity, information content, and network structure are considered. Contrary to previous\nstudies, in the proposed game, players find not only the most influential initial nodes but also the\nbest information content. The proposed novel game was implemented on a real data set where\nindividuals have different tendencies toward the players� options that change over time because of\ngaining influence from their neighbors and the information content they receive. This means that\ninformation content, the topology of the graph, and the individual�s initial tendency significantly\naffect the diffusion process. The proposed game is solved and the Nash equilibrium is determined\nfor a real data set. Lastly, the numerical results obtained from the proposed model were compared\nwith some well-known models previously reported in the literature.
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