Multiple fields, including computer science, political science, physics, epidemiology, biology, economics and social science, have independently tackled surprisingly related problems in the past, but are now joining forces to create a new science of the structure of large real-world networks. The course studies the connectedness of our social, technological and biological worlds through the lens of graphs and networks.
We will look into how people are connected in social networks; how opinions, disease and political activism (all very relevant in 2020) spreads through society; how communities form and can be inferred from data; theories underlying strong and weak ties in relationships; ranking of the web hyperlink graph (PageRank), and various other topics. We will study models and theory to help explain and exploit the structure of information and social networks. We will also discuss some tools to analyze these networks.