Groups and Networks

Understanding social groups and networks is a crucial component to understanding the nuances of interdependent behavior. The first aim of the class is to critically examine the theoretical approaches used to conceptualize the formation and performance of social groups as well as their dynamics from a social network perspective. The next part of the course will cover applied aspects of social network data collection and analysis including concepts such as sampling, descriptive statistics, and inferential models. We will discuss the design and implementation of field studies to answer research questions about community formation, homophily, and the spread of behavior and beliefs. The last part of the course will introduce students to agent-based modeling; We will study diffusion, contagion, and the emergence of norms using microsimulations. The course will wrap up with an overview of the presented theories, methods, and approaches of social network analysis and students will have the opportunity to reflect and synthesize about these overarching concepts. Please note: the course will draw from current literature and applied research and while some parts of the course will be taught in R and NetLogo, coding is not the primary focus of the course. Proficiency in R or NetLogo is not required.