Social Network Analysis

Catalog description

Methods of social network analysis used to examine patterns of ties among actors in a social system. This course provides an overview of the analytic methods and conceptual perspective of a social network approach to social science research, with a focus on quantitative methods. Social network analysis is used to examine patterns of ties between multiple actors in a social system, where the actors could be individuals, dyads, groups, organizations, or nation-states. There has been a dramatic rise in the application of such an approach to research from a broad range of researchers over the past decade. A social network approach is applicable to several subfields within sociology, such as social psychology, demography, criminology, organizations, and the family. The course objectives are to: 1) become familiar with the basic elements of social network analysis and recognize situations where this approach may be useful; 2) develop an appreciation for the conceptual perspectives behind this modeling approach; 3) learn about the strengths and limitations of network models and analyses; 4) apply social network analysis to empirical data and interpret findings, and finally: 5) complete a research paper that applies this approach to data regarding a social science problem. Network topics covered include centrality, clustering and cliques, triads and transitivity, weak ties, structural equivalence, and network visualization. In addition, students will be introduced to advanced topics, such as exponential random graph models, and dynamic SIENA models. Students should have completed two semesters of social statistics at the graduate level or equivalent before enrolling in this course.