About this Course

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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

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Advanced Level

Approx. 30 hours to complete

English

Skills you will gain

Social Network
Game Theory
Network Analysis
Network Theory

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Advanced Level

Approx. 30 hours to complete

English

Instructor

Instructor rating

4.88/5 (89 Ratings)

Matthew O. Jackson

Syllabus - What you will learn from this course

Content Rating96%(3,684 ratings)

Week

1

Week 1

4 hours to complete

Introduction, Empirical Background and Definitions

4 hours to complete

12 videos (Total 118 min), 3 readings, 3 quizzes

12 videos

An Introduction to the Course4m

1.1: Introduction9m

1.2: Examples and Challenges 15m

1.2.5 Background Definitions and Notation (Basic - Skip if familiar 8:23)8m

1.3: Definitions and Notation 14m

1.4: Diameter 16m

1.5: Diameter and Trees 6m

1.6: Diameters of Random Graphs (Optional/Advanced 11:12)11m

1.7: Diameters in the World 6m

1.8: Degree Distributions 13m

1.9: Clustering 8m

1.10: Week 1 Wrap2m

3 readings

Syllabus10m

Slides from Lecture 1, with References10m

OPTIONAL - Advanced Problem Set 110m

3 practice exercises

Quiz Week 130m

Problem Set 130m

Optional: Empirical Analysis of Network Data using Gephi or Pajek30m

Week

2

Week 2

4 hours to complete

Background, Definitions, and Measures Continued

4 hours to complete

11 videos (Total 105 min), 3 readings, 3 quizzes

11 videos

2.1: Homophily10m

2.2: Dynamics and Tie Strength 6m

2.3: Centrality Measures 14m

2.4: Centrality – Eigenvector Measures 13m

2.5a: Application - Centrality Measures 12m

2.5b: Application – Diffusion Centrality 6m

2.6: Random Networks 10m

2.7: Random Networks - Thresholds and Phase Transitions 7m

2.8: A Threshold Theorem (optional/advanced 13:00)13m

2.9: A Small World Model 7m

2.10 Week 2 Wrap3m

3 readings

Slides from Lecture 2, with references10m

OPTIONAL - Advanced Problem Set 210m

OPTIONAL - Solutions to Advanced PS 110m

3 practice exercises

Quiz Week 230m

Problem Set 230m

Optional: Empirical Analysis of Network Data30m

Week

3

Week 3

5 hours to complete

Random Networks

5 hours to complete

12 videos (Total 143 min), 3 readings, 4 quizzes

12 videos

3.1: Growing Random Networks17m

3.2: Mean Field Approximations 8m

3.3: Preferential Attachment 10m

3.4: Hybrid Models 14m

3.5: Fitting Hybrid Models 17m

3.6: Block Models 9m

3.7: ERGMs 9m

3.8: Estimating ERGMs 15m

3.9: SERGMs 9m

3.10: SUGMs 6m

3.11: Estimating SUGMs (Optional/Advanced 21:03)21m

3.12: Week 3 Wrap3m

3 readings

Slides from Lecture 3, with references10m

OPTIONAL - Advanced Problem Set 310m

OPTIONAL - Solutions to Advanced PS 210m

4 practice exercises

Quiz Week 330m

Problem Set 330m

Optional: Empirical Analysis of Network Data30m

Optional: Using Statnet in R to Estimate an ERGM30m

Week

4

Week 4

5 hours to complete

Strategic Network Formation

5 hours to complete

15 videos (Total 209 min), 3 readings, 2 quizzes

15 videos

4.1: Strategic Network Formation12m

4.2: Pairwise Stability and Efficiency 15m

4.3: Connections Model 11m

4.4: Efficiency in the Connections Model (Optional/Advanced 12:41)12m

4.5: Pairwise Stability in the Connections Model 6m

4.6: Externalities and the Coauthor Model 11m

4.7: Network Formation and Transfers 16m

4.8: Heterogeneity in Strategic Models 13m

4.9: SUGMs and Strategic Network Formation (Optional/Advanced 13:47)13m

4.10: Pairwise Nash Stability (Optional/Advanced 11:34)11m

4.11: Dynamic Strategic Network Formation (Optional/Advanced 11:57)11m

4.12: Evolution and Stochastics (Optinoal/Advanced 16:05)16m

4.13: Directed Network Formation (Optional/Advanced 16:38)16m

4.14: Application Structural Model (Optional/Advanced 35:06)35m

4.15: Week 4 Wrap4m

3 readings

Slides from Lecture 4, with references10m

OPTIONAL - Advanced Problem Set 410m

OPTIONAL - Solutions to Advanced PS 310m

2 practice exercises

Quiz Week 430m

Problem Set 430m

Week

5

Week 5

5 hours to complete

Diffusion on Networks

5 hours to complete

12 videos (Total 158 min), 3 readings, 3 quizzes

12 videos

5.1: Diffusion12m

5.2: Bass Model12m

5.3: Diffusion on Random Networks 9m

5.4: Giant Component Poisson Case 15m

5.5: SIS Model17m

5.6: Solving the SIS Model 9m

5.7: Solving the SIS Model - Ordering (Optional/Advanced 24:16)24m

5.8a: Fitting a Diffusion Model to Data (Optional/Advanced 22:47)22m

5.8b: Application: Financial Contagions (Optional/Advanced 12:47)12m

5.8c: Application: Financial Contagions - Simulations (Optional/Advanced 13:41)13m

5.9: Diffusion Summary 3m

5.10: Week 5 Wrap4m

3 readings

OPTIONAL - Advanced Problem Set 510m

OPTIONAL - Solutions to Advanced PS 410m

Slides from Lecture 5, with references10m

3 practice exercises

Quiz Week 530m

Problem Set 530m

Optional: Empirical Analysis of Network Data30m

Week

6

Week 6

3 hours to complete

Learning on Networks

3 hours to complete

9 videos (Total 100 min), 3 readings, 2 quizzes

9 videos

6.1: Learning26m

6.2: DeGroot Model 15m

6.3: Convergence in DeGroot Model 13m

6.4: Proof of Convergence Theorem (Optional/Advanced 10:25)10m

6.5: Influence 6m

6.6: Examples of Influence 8m

6.7: Information Aggregation 9m

6.8: Learning Summary 4m

6.9: Week 6 Wrap4m

3 readings

Slides from Lecture 6, with references10m

OPTIONAL - Advanced Problem Set 610m

OPTIONAL - Solutions to Advanced PS 510m

2 practice exercises

Quiz Week 630m

Problem Set 630m

Week

7

Week 7

4 hours to complete

Games on Networks

4 hours to complete

10 videos (Total 141 min), 4 readings, 2 quizzes

10 videos

7.1: Games on Networks12m

7.2: Complements and Substitutes 19m

7.3: Properties of Equilibria 14m

7.4: Multiple Equilibria 13m

7.5: An Application 7m

7.6: Beyond 0-1 Choices 20m

7.7: A Linear Quadratic Model 14m

7.8: RepeatedGames and Networks 24m

7.9: Week 7 Wrap 4m

7.9b: Course Wrap10m

4 readings

Slides from Lecture 7, with references10m

OPTIONAL - Advanced Problem Set 710m

OPTIONAL - Solutions to Advanced PS 610m

OPTIONAL - Solutions to Advanced PS 710m

2 practice exercises

Quiz Week 730m

Problem Set 730m

Week

8

Week 8

1 hour to complete

Final Exam

1 hour to complete

Reviews

4.8

162 reviews

5 stars
85.10%
4 stars
12.46%
3 stars
1.57%
2 stars
0.14%
1 star
0.71%

TOP REVIEWS FROM SOCIAL AND ECONOMIC NETWORKS: MODELS AND ANALYSIS

by HTDec 21, 2016

The course is vast. The Professor is to the point and doesn't lack knowledge in his field.

I'd recommend this course for anyone interested in Economics. Loved it.

by PVJun 20, 2017

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

by AWDec 6, 2020

Prof. Jackson is so good at explaining these concepts in the lectures. I have honestly learned a lot regarding this topic and academic area.

by SBOct 10, 2020

Very important course. My suggestion to the Prof. if he can increase the course length and include more details that would be much better or he can come up with advance course on the same series.

View all reviews

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Social and Economic Networks: Models and Analysis