Social networks are currently extremely popular, and social networks models are useful in studying network phenomena. This paper describes models that are flexible in form, applicable to binary, categorical, or ordered data, reflecting a single relation among actors or multivariate or...

This research examines four frequently used centrality indices — degree, closeness, betweenness, and eigenvectors — to understand the extent to which their clear theoretical distinctions are reflected in differences in empirical performance. Even for stylized networks in which one centrality...

This research uses random networks as benchmarks for inferential tests of network structures. Specifically, we develop formulas for expected values and confidence intervals for four frequently employed social network centrality indices. The first study begins with analyses of stylized networks,...

Among the many centrality indices used to detect structures of actors’ positions in networks is the use of the first eigenvector of an adjacency matrix that captures the connections among the actors. This research considers the seeming pervasive current practice of using only the first...