ABSTRACT
Social Network Analysis is widely used by the intelligence and operational communities to analyze relationships between individuals within groups of interest, and in many cases, used to monitor and possibly influence a network of interest. However, in order to analyze and monitor a network of interest, the network must first be characterized. Network models are mathematical tools with which to characterize a network and represent an efficient means with which to model, examine and analyze data from a particular social network. Therefore, any tools that can be quantitatively shown to help improve the characterization of a network into a network model are advantageous to the operations researcher. This chapter examines modern methods to characterize social networks for operational analysis and monitoring. These methods include both numerical and statistical approaches. Special emphasis will be given to theoretical statistical approaches currently emerging in modern literature. Such methods hold particular promise for network characterization as computational approaches typically do not scale well as a function of the size and edges that exist in particular networks. The chapter ends with a section on future directions as a means to discuss the rapidly evolving requirements of network characterization in this dynamic area of research.
