Speaker: Cameron Switzer, National Security Agency

Title: Analysis of Social Networks

Abstract:

The National Security Agency (NSA) is the nation's largest employer of mathematicians. From its formation, the NSA has recognized the high value of mathematics for solving difficult problems in cryptanalysis for its information assurance and signals intelligence missions. Today, mathematicians use their analytical skills to tackle some of the agency's most challenging security problems to help keep our nation safe. Social Network Analysis (SNA) is an area of data science that applies the mathematics of graph theory to analyze social structures. SNA techniques can be useful in the areas of sociology, anthropology, biology, economics, history, and political science, just to name a few. Centrality measures help identify important or influential individuals in social networks, and today, we'll discuss three of the most common ways to measure centrality: degree, closeness, and betweenness.

Cameron Switzer is an Applied Research Mathematician who works in the Research Directorate at the National Security Agency. While working towards her Bachelor's in mathematics at the University of Mississippi, she pursed research opportunities through the Sally McDonnell Barksdale Honors College and a Research Experience for Undergraduates (REU) funded by the National Science Foundation. She continued her education by earning a Master's in mathematics and joined the agency's Applied Mathematics Program (AMP) in 2011. The three year development program gave her the opportunity to take agency math classes and work in a variety of offices before settling into a permanent office after graduation in 2014.