报告题目：Social Network Analysis in the Framework of Structural Equation Modeling
报告人单位：University of Notre Dame
Social network data are increasingly collected in many fields of research, business, and government. For example, to study student behaviors, it is important to understand the context of behaviors because students are not independent entities but are typically connected with one another, which naturally leads to the collection and analysis of network data. This study proposes to combine structural equation modeling (SEM) techniques and data science methods to model network data. It tackles the complex problems of network data by treating them as new types of variables in SEM. We will show how to construct a SEM with networks and how to estimate such a model.
Dr. Zhiyong Zhang is a professor in Quantitative Psychology at the University of Notre Dame. His research aims to develop better statistical methods and software in the areas of education, health, management and psychology. He has conducted research in the areas of Bayesian methods, Big data analysis, Structural equation modeling, Longitudinal data analysis, Mediation analysis, and Statistical computing and programming. His most recent research involves the development of new methods for social network and text analysis. He is an associate editor of Multivariate Behavioral Research and Neurocomputing as well as the founding editor of Journal of Behavioral Data Science.