HETEROGENEOUS EPIDEMIOLOGIC INFLUENCE SPREADING MODELS IN COMPLEX NETWORKS

Abstract

Many of the systems around us are connected in networks with complex patterns forming a complex networks. The individuals of these networks interact among each other tending to impose theirs own state to the surrounding individuals. Such tendencies cause dynamic processes in complex networks defined as influence spreading. There is a big diversity of such processes, and their research gives important results for predicting the speed and rate of spreading of many processes like natural viruses, computer viruses, social processes etc.