What do computer networks, biological networks and social networks have in common?
Empirical studies of very disparate networked systems such as the Internet, social networks, and biological networks indicate the presence of
universal structural patterns. Researchers have then developed a variety of techniques to help us understand and predict the behavior of all these networks. In NETS 312, we study recent developments in this field, including such concepts as the small-world effect, degree distributions, clustering, network correlations, random graph models, models of network growth and preferential attachment, and dynamical processes taking place on networks.