  We study the diffusion behavior of real-time information. Typically,
real-time information is valuable only for a limited time duration, and hence
needs to be delivered before its "deadline." Therefore, real-time information
is much easier to spread among a group of people with frequent interactions
than between isolated individuals. With this insight, we consider a social
network which consists of many cliques and information can spread quickly
within a clique. Furthermore, information can also be shared through online
social networks, such as Facebook, twitter, Youtube, etc.
  We characterize the diffusion of real-time information by studying the phase
transition behaviors. Capitalizing on the theory of inhomogeneous random
networks, we show that the social network has a critical threshold above which
information epidemics are very likely to happen. We also theoretically quantify
the fractional size of individuals that finally receive the message. Finally,
the numerical results indicate that under certain conditions, the large size
cliques in a social network could greatly facilitate the diffusion of real-time
information.
