Experiments in Inferring Social Networks of Diffusion

Abstract

Information diffusion is a fundamental process that takes place over networks. While it is rarely realistic to observe the individual transmissions of the information diffusion process, it is typically possible to observe when individuals first publish the information. We look specifically at previously published algorithm NETINF that probabilistically identifies the optimal network that best explains the observed infection times. We explore how the algorithm could perform on a range of intrinsically different social and information network topologies, from news blogs and websites to Twitter to Reddit.