Statistics and Complex Networks: The Next Frontier

• Activity Number: 49
• Type: Invited
• Date/Time: Sunday, July 31, 2011 : 4:00 PM to 5:50 PM
• Sponsor: Section on Statistics in Defense and National Security
• Author(s): Eric Kolaczyk*+
• Companies: Boston University
• Keywords: graph ; network ; inference ; prediction ; sampling

Abstract

Over the past decade, the study of so-called `complex networks' -- that is, network-based representations of complex systems -- has taken the sciences by storm. Researchers from biology to physics, from economics to mathematics, and from computer science to sociology, are more and more involved with the collection, modeling and analysis of network-indexed data. With this enthusiastic embrace of networks across the disciplines comes a multitude of statistical challenges of all sorts. Although statistical methods and models have been developing in this area at a furious pace, most contributions have traditionally come from a wide spectrum of fields outside of statistics. Only in recent years has that begun to change, as statisticians have started to realize in growing numbers that complex networks likely represent one of the next major frontiers for our own field. In this talk I will outline the apparent nature of this new frontier, as well as some of the solutions beginning to emerge in my own work with colleagues, in the context of topics like network summary and visualization, network sampling, network modeling and inference, and network processes.