A novel game theoretic approach for modeling competitive information diffusion in social networks with heterogeneous nodes

Mehrdad Agha Mohammad Ali Kermani, Farshad Fatemi, Alireza Aliahmadi and Farnaz Barzinpour

Physica A: Statistical Mechanics and its Applications, 2017, vol. 466, issue C, 570-582

Abstract: Influence maximization deals with identification of the most influential nodes in a social network given an influence model. In this paper, a game theoretic framework is developed that models a competitive influence maximization problem. A novel competitive influence model is additionally proposed that incorporates user heterogeneity, message content, and network structure. The proposed game-theoretic model is solved using Nash Equilibrium in a real-world dataset. It is shown that none of the well-known strategies are stable and at least one player has the incentive to deviate from the proposed strategy. Moreover, violation of Nash equilibrium strategy by each player leads to their reduced payoff. Contrary to previous works, our results demonstrate that graph topology, as well as the nodes’ sociability and initial tendency measures have an effect on the determination of the influential node in the network.

Keywords: Social network; Influence maximization; Diffusion; Competition; Heterogenous nodes; Game theory (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:466:y:2017:i:c:p:570-582

DOI: 10.1016/j.physa.2016.09.038

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