Online influence maximization using rapid continuous time independent cascade model

Abstract

Do one really know the meaning of Online Influence (OI) Maximization? Do you know why do we need to calculate the influence of social networking sites? How to measure the influence of online maximization? How does it really works? If you have been pondering for the answers of the questions then this paper will assist you to identify and connect with influences of online maximization. Influence Maximization is the problem in which subset of seed nodes are found within the social networks which maximizes influence on other nodes in their ties and relationships. Influence maximization has been developed to find out how influence gets propagated through its network. The concept of Influence Maximization lies in the selection of minimal set of seed nodes which propagates maximum of its influenciality within a network. This paper firstly comprises of previous models used in appropriate selection of seed nodes i.e. Linearly Threshold Model (LT), Classic Cascade Independent s Model(IC), Extended Classic Independent Model(EIC). Then, I proposed a new Model Rapid Continuous Time (RCT) Independent Cascade Model that can be used in the Classic Independent Model(IC).