Title: Characterizing information importance and the effect on the spread in various graph topologies,
Abstract: In this paper we present a thorough analysis of the nature of news in
different mediums across the ages, introducing a unique mathematical model to
fit the characteristics of information spread. This model enhances the
information diffusion model to account for conflicting information and the
topical distribution of news in terms of popularity for a given era. We
translate this information to a separate graphical node model to determine the
spread of a news item given a certain category and relevance factor. The two
models are used as a base for a simulation of information dissemination for
varying graph topoligies. The simulation is stress-tested and compared against
real-world data to prove its relevancy. We are then able to use these
simulations to deduce some conclusive statements about the optimization of
information spread.