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Modeling and analyzing information diffusion behaviour of social networks

This paper analyzes the information diffusion behaviour of social network by studying the behaviour of infection flow in a social network where social network is modeled by Erdos Renyi method. Erdos Renyi model create the links (edges) in the network on the basis of two main parameters, number of nodes and average degree of the network. Infection in social network are information contents in any of the form like text, images, audio, video, animation etc. There are two main methods for spreading of content over web; conserved spread (SIS model) and non conserved spread (SIR model). This paper uses SI (Susceptible-Infected) model. Infection flow behaviour is analyzed by taking the data i.e. no of infected nodes of a social network in NetLogo environment and simulated for a different size and different average degree network taking input 100 times which helps in correction of data and improves the accuracy of the results. This paper shows that the information diffusion takes place highly between a particular range of average degree for any size network.