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
Status: Social Sciences
Social Sciences
Status: Sociology
Sociology
Advanced·Course·30 hours
Featured reviews
5.0
·Reviewed Sep 6, 2020
Dr. Jackson is clear and concise in his explanations and did a great job creating a high-level overview course on a subject for which he obviously has a much greater wealth of knowledge.
5.0
·Reviewed Sep 3, 2016
The course is a helpful first step in the field of network science. Presenting clearly many complex ideas that are important for understanding current research.
5.0
·Reviewed Oct 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.
5.0
·Reviewed Apr 29, 2017
An overview of concepts and models of how networks form. There are applicable with basic concepts from probability theory, statistics, and some light calculus astonishingly well.
5.0
·Reviewed Aug 24, 2022
very helpful in understanding how idealized network models explain the observations in the real world; also got insights on the methodology in social science
5.0
·Reviewed Aug 8, 2016
Very good course on Social Networks, and also a hard one even for graduate level. Generally assignments are not too tough but fully understanding all the concepts take lots of extra readings.
5.0
·Reviewed Jun 24, 2016
A very usefull course very different from others. Although for coursera standars, its very extensive and not so basic, that´s why I think its great
5.0
·Reviewed Jan 11, 2025
Thanks Professor Jackson for your generosity of sharing this course on Coursera. It's an excellent start for students interested in research on social networks analysis.
4.0
·Reviewed Dec 9, 2018
Excellent course. The labs are the best. Pajek and Gephi will be handy for network graphing and analyzing data. Thank you Professor Matthew Jackson. Your work is very good for reference.
5.0
·Reviewed Jun 20, 2017
An excellent and very useful course. Recommend with no reserves to anyone willing to understand the world from a well structured perspective
5.0
·Reviewed Apr 16, 2018
Great survey course for social network analysis. Dr. Jackson's lectures motivated me to buy the book, and I hope to come back to this course later to work more on the optional parts.
5.0
·Reviewed Dec 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.
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M
Michael
5.0
·Reviewed Apr 16, 2018
Great survey course for social network analysis. Dr. Jackson's lectures motivated me to buy the book, and I hope to come back to this course later to work more on the optional parts.
I
Isard
5.0
·Reviewed May 15, 2019
Dear Matthew,
Thank you so much for a wonderful introduction to social and economic networks. Your lectures were wonderful. Your choice of topics was superb and your top-notch pedagogical skills show through when you explain difficult concepts with disarming simplicity. I had no idea that your course will be so enjoyable. Thank you for introducing me to this fascinating subject. Now, at least I have some rudimentary understanding of this field and will dig further to incorporate networking tools in my research.
The videos are high quality and it is such a blessing to have the replay option. The cure for senior moments is to use replays. I can't wait for your followup: advanced topics in networking. Thanks, Isi
S
Sanjoy
5.0
·Reviewed Oct 11, 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.
N
Nikita
5.0
·Reviewed May 29, 2020
The course is extremely well-structured and very well in-depth. The beginning is smooth and very carefully put together which makes it really interesting and hard to drop. This interest is also pulled further as we go deeper into social networks and their modelling. A lot of fundamental economic subjects of utility maximization, game theory, rationalization, etc are explained in a simple yet accurate manner. The course is solely enhanced multiple folds due to the instructor as he is very precise, clear and crisp with his explanations and is extremely well-researched. The clarity of thought and his method of explaining even complex mathematical forms and derivations so easily by breaking them down makes the course a lot easier and interesting, even for a person who does not possess a higher level of skill in mathematics. I would love to take up another course by the same instructor.
Overall, I absolutely do not see room for criticism in this course nor with the teacher.
Thank you, as this was extremely helpful and interesting.
T
THANACHON
5.0
·Reviewed Apr 29, 2017
An overview of concepts and models of how networks form. There are applicable with basic concepts from probability theory, statistics, and some light calculus astonishingly well.
M
Manoel
5.0
·Reviewed Nov 2, 2017
Really enjoyed this course. The professor is really good and covers quite a lot of ground during the lectures. Good way to get into complex networks! Probably gonna do some studying on my own now :)
S
Siqi,
5.0
·Reviewed Aug 8, 2016
Very good course on Social Networks, and also a hard one even for graduate level. Generally assignments are not too tough but fully understanding all the concepts take lots of extra readings.
L
Laurent
5.0
·Reviewed Mar 1, 2018
Prof. Jackson is an outstanding teacher, and I very much enjoyed this course. I come from a probability background (PhD) but never looked at graphs or networks before. I thought that the course was very well made, with a perfect balance between theoretical concepts and practical applications. I also think that Prof. Jackson's treatment of mathematical concepts is entirely optimal given the diverse audience he most likely has: it is technical, but definitely not going into the more formal details you would get in a math course. I think this is great, because for the more math-oriented people it's just an occasion to look up some references, or think about a more formal way of expressing the concepts in question, while it does not overwhelm those who don't want to go through a bunch of existence theorems. By all counts, an outstanding course.
T
Thiago
5.0
·Reviewed Jun 21, 2022
This course provides a solid foundation to start exploring the world of networks. The lessons are thorough and the professor clearly has many years of experience in the topic, as he is able to anticipate questions and pitfalls that are common to beginners. Still, I should warn anyone interested in this course that it requires a great dose of mathematics, from linear algebra to differential calculus. No calculation is particularly difficult, but if you are rusted (as I was) and want to understand where the models came from, the course can take much longer to be completed. I believe this course is most suited to researchers and students with a quantitative background that would like to expand their theoretical and methodological views.
A
Alfredo
5.0
·Reviewed Sep 17, 2022
One of the best courses I ever made on Coursera. Profound, informative and entretaining. Covers from learning to social networks, from mathematics to economy. Professor Jackson, with extraordinary didactic, teaches in a way you can grasp the meaning of the most complicated mathematical problems, so Google Page number, externalities, Pareto Effieciency, consensus, Nash equilibrium, homophily, and state transitions will be reached in a logical and self-contained percourse. Most of all, the course made me feel back in the engineering school, the fun of discovering new worlds and acquiring new skills.
N
Noah
5.0
·Reviewed Nov 17, 2018
A very comprehensive course, taught in a very engaging manner by a top-caliber researcher and professor. An improvement would be adding a separate problem set for each lecture topic, to more thoroughly test specific understanding immediately after the teaching. Also, some of the Gephi instructions were not quite clear enough.
Getting Prof. Jackson's book as a companion to this course is very useful.
T
Tongtong
5.0
·Reviewed Dec 5, 2016
Excellent course for both advanced micro theory PhD learners who wants to go deep into the prove and master (and up) level learner who wants to have a flavour of Network Theory. Professor Jackson is great in interpreting the intuition behind the theory and prove. This 8 weeks are great learning experience for me!
L
Lillian
5.0
·Reviewed Jul 3, 2021
I was new to network theory but the concepts were very well articulated. A whole new way of looking at what makes social relationships, favor exchange(s) and social networks work. Well worth the time.
A
antonio
5.0
·Reviewed Apr 22, 2021
Very well done and explained, full of insight in the social network analysis!!! Lots of ideas about using it in company and team behaviours! Economical analysis of financial contagion is insightful!!!
J
Julia
5.0
·Reviewed Apr 18, 2020
heavy stuff, especially if you're not that deep into the mathematics, but great overview. It will give you a better understandig of SNA. I miss the economical examples though.
G
Gabriel
5.0
·Reviewed Jun 25, 2016
A very usefull course very different from others. Although for coursera standars, its very extensive and not so basic, that´s why I think its great
J
Jess
5.0
·Reviewed Jul 13, 2017
I got a lot out of the course. However, there are still several concepts I'm really, really fuzzy on, such as Pareto efficiency, games on networks, Nash stability, & strategic complements/substitutes. I've already directly applied the lessons from the course to work I'm doing, but it's frustrating that there isn't some kind of office hours or way to sit down with someone and go through these concepts one step at a time. I get the general concept of all of them, but I look at some things and end up at different conclusions because I'm missing something. That's not a statement about this course, it's just the reality of taking online courses. I know if I could walk through it and see where the logic is off, I'd get it better.
W
Wilson
5.0
·Reviewed Oct 8, 2023
Professor Jackson's class was an enjoyable learning experience for me. I read his "The Human Network" and "Social and Economic Networks" as the class lecture notes and lectures, though well written and well taught respective, are at times a little difficult for me to get all the concepts straight. The best part of the course was how it shows the various mathematical modeling could be done for social/economic networks. The last part on Game Theory was a little rushed.
The way this class was structured was to allow different people to capture the material at different levels. Quiz and exams were quite easy, and I feel that more exercise problems could help.
R
Raphael
5.0
·Reviewed Mar 3, 2022
Fantástico! As aulas são ministradas com os journals(papers) do próprio autor com sua vasta expertise no campo, sendo uma suma autoridadeno assunto. Temos a grandiosidade e majestosa humildade em ser um ótimo divulgador cientifíco, por meio de abordagens simples que demonstram ideias complexas recheadas de formalismo, as quais podem ser compreendidas por um público mais amplo. O curso tem alguns anos e continua sendo imprecindível para aqueles que almejam aperfeiçoar em SNA(Social Network Analysis). Temos uma boa base teórica sólida sobre diversos temas desta área com algumas discussões ricas entre resultados recentemente publicados nos últimos anos.
R
Rebecca
5.0
·Reviewed Jan 13, 2022
I decided to take this course after taking Princeton's Global Systemic Risk (GSR). They are perfect complements, if that is what you are interested in. While this course is more modelling and data oriented, the GSR course applies that information and shows you how you can use the data you have gathered in a very directed manner. I am more of let us apply the data gathered and would happily leave the modelling to someone else, but it was interesting to learn how the data is gathered.