Social Network Analysis plays an increasingly important role in fields as diverse as sociology, political science, economics, health, psychology, history, literature, business, marketing, biology, and ethno-musicology.

This course will examine the key papers in the development of SNA, and will develop the methodological tools needed to model and predict networks and use them in the social sciences.

Course Description:

Social networks have always been at the center of human interaction, but especially with the explosive growth of the internet, network analysis has become increasingly central to all branches of the social sciences. How do people influence each other, bargain with each other, exchange information (or germs), or interact online? A diverse array of deep questions about human behavior can only be answered by examining the social networks encompassing and shifting around us. Network analysis has emerged as a cross-disciplinary science in its own right, and has in fact proven to be of even greater generality and broader applicability than just the social, extending to ecology, physics, genetics, computer science, the humanities, and other domains.

This course will examine key papers in the development of social network analysis, and will develop the theory and methodological tools needed to model social networks in domains as diverse as sociology, political science, economics, health, psychology, history, and business. Students will learn the essential tools of network analysis, from centrality, homophily, and community measurement, to random graphs, network formation, information flow, and strategic games. Alongside this we will read a series of seminal papers, shaped in part by the substantive interests of the students and their various backgrounds, with a particular focus towards developing individual student research papers using network analysis methods.