Blocking negative influential node set in social networks: From host perspective

Nowadays, social networks are considered as a very important medium for the spreading of information, innovations and ideas etc. among individuals using Viral Marketing (VM) but the key problem with VM is to find the set of influential users, who, when convinced to adopt an innovation or idea, shall influence other users in the network, leading to large number of adoptions. Therefore, in our study we propose and study the competitive viral marketing problem from the host perspective, where the host of the social network sells the viral marketing campaigns to its customers and keeps control of the allocation of seeds. We propose a new diffusion model considering the host perspective in Social Networks where the network model will have both positive and negative edges. We then propose a novel problem, named Blocking Negative Influential Node Set (BNINS) selection problem, to identify the positive node set such that the number of negatively activated nodes is minimized for all competitors from host perspective. We first provide our newly proposed diffusion model, define the novel BNINS problem, propose a solution sketch to the problem and propose simulations procedure to validate the proposed solution.