Analysis of information diffusion in dynamic information networks

Dynamic information network is a social network in which data and topology continuously keeps on changing. Number of users are approaching and departing the social networks and share information. Information diffusion plays a key role in this information sharing. So it is very important to understand the process of information diffusion in this type of network. It also helps to analyze the effective design of advertising campaigns, viral marketing and recommender systems. In this paper two major models of information diffusion i.e. Independent Cascade Model and Linear Threshold Model are studied and implemented with respect of dynamic information network While these methods gave promising results on static networks, but because of their linear and scalable properties, they are insufficient to model dynamic information networks.