Exploring Intelligent Approach of Influence Minimization Considering the Node Surveillance in Online Social Networks

Attractive information such as innovations, awareness campaigns, branding, and advertising help people positively. Whereas, awful information such as rumors, malicious viruses, pornography, and revenge disturb people. The negative information contributes to chaos among people; therefore, it is to be blocked and hinder from further diffusion. This has motivated us towards the study of the problem named influence minimization. As the real world network can be modeled to a multilayer network, we focus our study towards the information diffusion through a multilayer network. Each node assigns a threshold, and its variation affects the rate of influence propagation across the network. In the influence minimization problem, the energy level of each node changes that help to formulate the function that minimizes the influence propagation. By applying two reduction policies, we are able to optimize our objective of minimizing the influence towards repulsive information. In this article, we consider the user response and its surveillance in the network. Repeated experiments on real networks has helped us to validate the proposed methods.