Analysis of social, spatial, and complex networks

Objectives

The course begins with an overview of concepts used to describe and measure networks. We will then discuss a series of models on network formation. Students will get familiarized with programs and packages that are commonly used for analyzing and simulating networks (gephi, R – igraph, Python – networKx). We will later discuss how networks impact individual behavior and collective outcomes, including contagion, diffusion, and public good provision.

Course outline

Chapter 1. Introduction: representing a network and basic definitions

Chapter 2. Global and local measures and statistics on networks

Chapter 3. Random network formation models

Chapter 4. Strategic network formation

Chapter 5. Contagion and epidemics on networks

Chapter 6. Decisions, behavior, and games on networks

Prerequisites

Mathematics, economics and game theory. For example, it will be assumed that students are comfortable with basic concepts from linear algebra (e.g., matrix multiplication), probability theory (e.g., probability distributions, expected values), and game theory (e.g., games in normal form, in extensive form, strategy, equilibrium), and some light calculus (e.g., differentiation and integration)​