About this course: 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 does their structure 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. You can find a more detailed syllabus here: http://web.stanford.edu/~jacksonm/Networks-Online-Syllabus.pdf You can find a short introductory videao here: http://web.stanford.edu/~jacksonm/Intro_Networks.mp4

Who is this class for: The course is aimed at people interested in researching social and economic networks, but should be accessible to advanced undergraduates and other people who have some prerequisites in mathematics and statistics. 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, Bayes' rule), and statistics (e.g., hypothesis testing). Beyond those concepts, the course is self-contained.

Created by: Stanford University

Taught by: Matthew O. Jackson, Professor
Economics

Level	Advanced
Language	English
How To Pass	Pass all graded assignments to complete the course.
User Ratings	4.8 stars Average User Rating 4.8See what learners said

Syllabus

WEEK 1

Introduction, Empirical Background and Definitions

Examples of Social Networks and their Impact, Definitions, Measures and Properties: Degrees, Diameters, Small Worlds, Weak and Strong Ties, Degree Distributions

12 videos, 3 readings, 2 practice quizzes

Graded: Problem Set 1

WEEK 2

Background, Definitions, and Measures Continued

Homophily, Dynamics, Centrality Measures: Degree, Betweenness, Closeness, Eigenvector, and Katz-Bonacich. Erdos and Renyi Random Networks: Thresholds and Phase Transitions

11 videos, 3 readings, 2 practice quizzes

Graded: Problem Set 2

WEEK 3

Random Networks

Poisson Random Networks, Exponential Random Graph Models, Growing Random Networks, Preferential Attachment and Power Laws, Hybrid models of Network Formation.

12 videos, 3 readings, 3 practice quizzes

Graded: Problem Set 3

WEEK 4

Strategic Network Formation

Game Theoretic Modeling of Network Formation, The Connections Model, The Conflict between Incentives and Efficiency, Dynamics, Directed Networks, Hybrid Models of Choice and Chance.

15 videos, 3 readings, 1 practice quiz

Graded: Problem Set 4

WEEK 5

Diffusion on Networks

Empirical Background, The Bass Model, Random Network Models of Contagion, The SIS model, Fitting a Simulated Model to Data.

12 videos, 3 readings, 2 practice quizzes

Graded: Problem Set 5

WEEK 6

Learning on Networks

Bayesian Learning on Networks, The DeGroot Model of Learning on a Network, Convergence of Beliefs, The Wisdom of Crowds, How Influence depends on Network Position..

9 videos, 3 readings, 1 practice quiz

Graded: Problem Set 6

WEEK 7

Games on Networks

Network Games, Peer Influences: Strategic Complements and Substitutes, the Relation between Network Structure and Behavior, A Linear Quadratic Game, Repeated Interactions and Network Structures.

10 videos, 4 readings, 1 practice quiz

Graded: Problem Set 7

WEEK 8

Final Exam

The description goes here

Graded: Final

FAQs

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Coursework

Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.

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Creators

Stanford University

The Leland Stanford Junior University, commonly referred to as Stanford University or Stanford, is an American private research university located in Stanford, California on an 8,180-acre (3,310 ha) campus near Palo Alto, California, United States.

Ratings and Reviews

Rated 4.8 out of 5 of 170 ratings

An excellent and very useful course. Recommend with no reserves to anyone willing to understand the world from a well structured perspective

This course is quite helpful as network theory can be applied in epidemiology, economics, sociology and even physics. I would recommend this to anyone who wishes to learn how a certain group of subjects act in real world situations.

Matt is the simple the best! We've covered a lot of different models and examples. Probably the best networks course that you can take.

best

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Social and Economic Networks: Models and Analysis

Social and Economic Networks: Models and Analysis

Social and Economic Networks: Models and Analysis