Markov Chain Model Representation of Information Diffusion in Social Networks

The spread of information in a social network has received renewed interest as social media becomes an increasingly popular channel of communication. We are interested in the phenomenon of social diffusion of a piece of information in the presence of a contradicting information in the network. Specifically we explore the use of formal methods for verification in studying this phenomena. Using Monte Carlo simulation and the probabilistic model-checker (PRISM) we are able to represent social networks and confirm an earlier conjecture that disseminating new information rapidly is resistant to the presence of contradicting information.