Maryam Adineh - Department of Computer Engineering, Ferdowsi University of Mashhad, Mashhad, Iran.
Mostafa Nouri Baygi - Department of Computer Engineering, Ferdowsi University of Mashhad, Mashhad, Iran.

The problem of influence maximization is selecting the most influential individuals in a social network. With the popularity of social network sites and the development of viral marketing, the importance of the problem has increased. The influence maximization problem is NP-hard, and therefore, there will not exist any polynomial-time algorithm to solve the problem unless P = NP. Many heuristics are proposed for finding a nearly good solution in a shorter time. This study proposes two heuristic algorithms for finding good solutions. The heuristics are based on two ideas: ۱) vertices of high degree have more influence in the network, and ۲) nearby vertices influence on almost analogous sets of vertices. We evaluate our algorithms on several well-known data sets and show that our heuristics achieve better results (up to ۱۵% in the influence spread) for this problem in a shorter time (up to ۸۵% improvement in the running time).

Degree centrality, Heuristic algorithm, Independent cascade model, Influence maximization