About this Course

55,999 recent views

Learner Career Outcomes

25%

started a new career after completing these courses
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Advanced Level
Approx. 25 hours to complete
English
Subtitles: English

Skills you will gain

Social NetworkGame TheoryNetwork AnalysisNetwork Theory

Learner Career Outcomes

25%

started a new career after completing these courses
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Advanced Level
Approx. 25 hours to complete
English
Subtitles: English

Instructor

Offered by

Stanford University logo

Stanford University

Syllabus - What you will learn from this course

Content RatingThumbs Up96%(3,049 ratings)Info
Week
1

Week 1

3 hours to complete

Introduction, Empirical Background and Definitions

3 hours to complete
12 videos (Total 118 min), 3 readings, 3 quizzes
12 videos
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 128m
Problem Set 112m
Optional: Empirical Analysis of Network Data using Gephi or Pajek8m
Week
2

Week 2

3 hours to complete

Background, Definitions, and Measures Continued

3 hours to complete
11 videos (Total 105 min), 3 readings, 3 quizzes
11 videos
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 216m
Problem Set 210m
Optional: Empirical Analysis of Network Data6m
Week
3

Week 3

4 hours to complete

Random Networks

4 hours to complete
12 videos (Total 143 min), 3 readings, 4 quizzes
12 videos
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 326m
Problem Set 36m
Optional: Empirical Analysis of Network Data4m
Optional: Using Statnet in R to Estimate an ERGM6m
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
4.2: 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 436m
Problem Set 414m

Reviews

TOP REVIEWS FROM SOCIAL AND ECONOMIC NETWORKS: MODELS AND ANALYSIS

View all reviews

Frequently Asked Questions

  • Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:

    • The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
    • The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
  • When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

  • You will be eligible for a full refund until two weeks after your payment date, or (for courses that have just launched) until two weeks after the first session of the course begins, whichever is later. You cannot receive a refund once you’ve earned a Course Certificate, even if you complete the course within the two-week refund period. See our full refund policy.

  • Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You’ll be prompted to complete an application and will be notified if you are approved. Learn more.

More questions? Visit the Learner Help Center.