Social Network / Fall 2025

Course Description

This course provides a comprehensive introduction to Network Science, an emerging interdisciplinary field that offers a new paradigm for understanding our highly connected world, where we increasingly recognize that nothing happens in isolation. Moving beyond traditional reductionist approaches, we will explore the simple yet far-reaching natural laws that govern the structure and evolution of the complex networks that underpin social, biological, and technological systems. The central goal is to equip you with the ability to "think network"—to analyze the world as a set of actors and the relationships connecting them, and to understand how network structure fundamentally shapes dynamic processes like the spread of information, economic stability, and public health. Grounded in the mathematical language of Graph Theory, the course investigates the foundational models that describe network topology, including Erdos-Renyi random graphs, the Watts-Strogatz "small-world" model, and the Barabasi-Albert "scale-free" model of growth and preferential attachment. We will analyze key structural properties such as centrality measures, community structure, and robustness, and then progress to dynamic processes like structural balance, information cascades, and the diffusion of epidemics and opinions.