Social network analysis is becoming increasingly popular in social, educational, and psychological sciences. This interactive course intends to provide participants with a detailed introduction, practical examples, and demonstration of analyzing social network data using the free software R. Topics covered include (1) Network Data; (2) Network Visualization; (3) Network Statistics; (4) Basic and Advanced Network Models. Especially, we will cover classical models such as Stochastic Block Model, Exponential Random Graph Model, Latent Space Model, and the newly developed techniques such as Latent Factor Space Modeling and Network Mediation Analysis.
Dr. Haiyan Liu is currently an assistant professor of Quantitative Methods, Measurement, and Statistics at the University of California, Merced. Dr. Liu’s research centers broadly on statistical modeling of psychological and behavioral data such as high-dimensional data, longitudinal data, and categorical data. Her recent research includes social network modeling, Bayesian structural equation modeling, and non-parametric modeling of growth curves.
- Instructor: Haiyan Liu