Abstract by Matthew Steffen
Family Networks and Measurements of Centrality
Most real-world networks, including most social, biological, and technological networks, do not have a local tree-like structure. The exception is family networks. Due to a lack of literature on the topic, our goal is to begin by determining which types of measures or metrics are useful in analyzing such systems. The standard measures we consider to analyze these networks are degree centrality, eigenvector centrality, etc. Statistical tools such as the Kendall Tao scores relate the different centralities and show us which measurements remain constant along the variety of graphs and which differ. These differences in the scores demonstrate the impact that the local tree-like structure can have on the overarching structure and therefore determine the behaviors specific to the family network.