Influence maximization in social networks: Considering both positive and negative relationships

Now a days, the viral marketing has been extensively increased on online social networks, thus increasing the research work on the influence maximization algorithms in social networks. Motivated by this viral marketing strategies, many of the researches proposed few fundamental algorithms to find the subset of individuals to promote a product where the goal is to trigger maximum number of individuals in the network. The problem here is which subset of individuals to pick and why? This problem has been studied by many researches. However, those studies focused on social networks with friendship relations, but to be practical the foe relationship also exists in social networks. Our study is to propose a new diffusion algorithm considering both the friend and foe relationship types in online social networks (OSNs), where the network model would be with both positive and negative edges. We first provide our newly proposed diffusion model, define the influence maximization problem i.e. Positive Opinion Influential Node Set (POINS) selection problem, provide the solution for POINS problem and perform simulations to the social networks with both friend and foe relationships.