Social Network Analysis for Business Applications
Go beyond the traditional clustering and predictive models to identify patterns in your business data. Social network analysis describes customers' behavior but not in terms of their individual attributes. Rather than basing models on static individual profiles, social network analysis depicts behavior in terms of how individuals relate to one another. In practical terms, this approach highlights connections between individuals and organizations and how important they might be in viral effect throughout communities and particular groups. For business purposes, social network analysis can be employed to avoid churn, diffuse products and services, and detect fraud and abuse, among many other applications.
In this course, you will learn how to build networks from raw data. You will also learn about the various approaches for analyzing your customers, focusing on their relationships and connections within the network. This course enables you to improve business performance and better understand how your customers are using products and services. In addition to the network analysis approach to linking distinct entities, playing different roles on particular connections, this course will also show you a set of network optimization algorithms that you can use to solve a variety of complex business problems. Methods such as minimum-cost network flow, shortest path, linear assignment, minimum spanning tree, eigenvector, and transitive closure are presented in a business perspective for problem solving.
Exercises or hands-on workshops are included with most SAS courses.