Introducing individual biases, trust, and information freshness for competitive information diffusion model in social networks

This paper analyzes information diffusion, focusing mainly on competitive information within social networks. We introduce realistic factors, namely, the polarity of an individual towards a particular information, the level of trust between persons, and the decaying freshness of information in the network. We presented a model by incorporating these factors with the Susceptible-Infected-Recovered (SIR) model as a basis. We developed a web-based interface to simulate the model on user-uploaded graphs. The application simulates the spread of information based on the values of the user-defined parameters and generates a comprehensive visual report. Provision for simultaneously submitting multiple simulation jobs is also provided. We reported experimental results on several synthetic and real-world networks using the developed simulation platform.