Social and Economic Networks: Models and Analysis

Course Overview

Learn how to model social and economic networks and their impact on human behavior. How do networks form, why do they exhibit certain patterns, and how do their structures impact diffusion, learning, and other behaviors? We will bring together models and techniques from economics, sociology, math, physics, statistics, and computer science to answer these questions. The course begins with some empirical background on social and economic networks, and an overview of concepts used to describe and measure networks. Next, we will cover a set of models of how networks form, including random network models as well as strategic formation models, and some hybrids. We will then discuss a series of models of how networks impact behavior, including contagion, diffusion, learning, and peer influences.

Description

Empirical Background, and Definitions, Examples of Social Networks and their Impact, Definitions, Measures, and Properties: Degrees, Diameters, Small Worlds, Weak and Strong Ties, Homophily, Dynamics, Centrality Measures: Degree, Betweenness, Closeness, Eigenvector, and Katz-Bonacich. Erdos and Renyi Random Networks: Thresholds and Phase Transitions, Book Readings: Social and Economic Networks, The Human Network, Poisson Random Networks, Exponential Random Graph Models, Growing Random Networks, Preferential Attachment, and Power Laws, Hybrid models of Network Formation. Book Readings: Social and Economic, Game-Theoretic Modeling of Network Formation, The Connections Model, The Conflict between Incentives and Efficiency, Dynamics, Directed Networks, Hybrid Models of Choice and Chance. Diffusion on Networks, Empirical Background, The Bass Model, Random Network Models of Contagion, The SIS model, Fitting a Simulated Model to Data.