Interface Implementation for Quantifying Information Spread on Social Networks

Social media today, has grown into a vital facet of modern human existence. A remarkable amount of the information reaching us comes in the form of posts and messages on social media. As a result of the ever-growing social media, it has turned into an essential scheme for viral marketing and influencing the masses. Hence, it becomes imperative to discern how information spreads on such networks and how much. The methodology suggested in the Restrained-Susceptible-Infected-Recovered (RnSIR) Model enables us to calibrate the spread of knowledge and material on networks. This paper proposes an interface which uses the calculations given by the RnSIR model. Essentially, this interface prompts users to give a network interaction data set as the input and outputs the information dispersion on inputted network. It uses the same algorithms to do this as the RnSIR model.