Odum Institute: Social Network Analysis

Social Network Analysis: Description and Inference

This one-day course will be offered via Zoom. Attendance is required as the course will not be recorded.

Course Summary:

This course will provide an introduction to descriptive and inferential network analysis. In the morning we will cover descriptive network analysis, including: terminology, data collection/management, position (e.g., centrality) analysis, visualization, and community detection. In the afternoon we will cover statistical network analysis. Do actor attributes such as gender, race, or political preferences salary predict tie formation in a network? Does the network exhibit a tendency towards reciprocal tie formation? Statistical network models can be used to empirically study network structure and answer questions such as these. We will cover both empirical analysis and network simulation using statistical network models. Real-world network data and R code will be presented through interactive workshop sessions in both the morning and afternoon. There are no formal prerequisites for the course, but a background in basic statistical analysis (e.g., regression) will be useful.

Instructor: Bruce Desmarais, PhD

Bruce Desmarais, PhD, is the DeGrandis-McCourtney Early Career Professor in Political Science, Associate Director of the Center for Social Data Analytics, and an Affiliate of the Institute for Computational and Data Sciences at Penn State University. His research is focused on methodological development and applications that further our understanding of the complex interdependence that underlies politics and public policy. Methodologically, he focuses on methods for modeling networks, analyzing text, and running experiments on social systems. Primary application areas of interest to Bruce include public policy diffusion and digital communications involving political elites.

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