  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.
