Information diffusion in social networks is often characterized by huge participating
communities and viral cascades of high dynamicity. To observe, summarize, and understand
the evolution of dynamic diffusion processes in an informative and insightful way is a
challenge of high practical value. However, few existing studies aim to summarize networks
for interesting dynamic patterns. Dynamic networks raise new challenges not found in static
settings, including time sensitivity, online interestingness evaluation, and summary …

Social media forms a central domain for the production and dissemination of real-time
information. Information diffusion is fundamental process taking place in social network.
While it is often possible to directly observe when nodes become infected or publish the
information, observing individual transmissions (who infects whom, or who influences
whom) is typically very difficult. Furthermore, in many applications, the underlying network
over which the diffusions and propagations spread is actually unobserved. A key tool in this …