Course Description
Social network analysts consider relations to be the focal units of analysis – and the bases of social structure. This course surveys a mixture of mathematical and statistical techniques for analyzing social networks. Students will gain a working knowledge of relevant software packages and common approaches to network analysis.
Athena Title
NETWORK ANALYSIS
Grading System
A - F (Traditional)
Course Objectives
Students will gain a working knowledge of relevant software packages and common approaches to network analysis. Students will become comfortable using the dedicated social network software package UCINET, conducting network analysis in general statistical packages such as STATA, and using the R programming environment for analyzing social networks.
Topical Outline
1. Basic Graph Theory 2. Centrality and Centralization 3. Blockmodeling and Structural Equivalence 4. Role Algebra 5. Clustering Analysis and Multi-dimensional Scaling 6. Multi-mode and Multi Level Network Analysis 7. Log-linear Models 8. Matrix Comparison Using Quadratic Assignment Procedures (QAPP) 9. Exponential Random Graph (ERG) Models 10. Regression Approaches for Egocentric Network Data
Syllabus
Public CV