Implementation of the RnSIR Model

Abstract

By etymology, the word viral stems from virus, a term used to describe the spread of effect of infectious symptoms across organisms. On the internet, a piece of content can spread similar to a virus, making people infected as and when they come in contact with it. The infection usually occurs when the user shares it, with its circle of friends and associates on a social network. However, it is possible to predict the reach of information across a number of users in a directed network data set. This is possible through the proposed interface which uses the calculations proposed in the Restrained-Susceptible-Infected-Recovered (RnSIR) model. The interface accepts a data set as an input from the users whilst giving the percentage of information spread in that network as the output. The calculations at the interface back-end are done by using the same algorithms as used by the RnSIR model, to select influential nodes and then calculate the said percentage using them with the help of an algorithm. The interface poses to be useful for tracking the spread of information in a directed network for social media marketing and peripheral tactics.