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...

Nov 02, 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 :)

Aug 09, 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.

篩選依據：

創建者 Isard D

•May 16, 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

創建者 Llewellyn P

•Apr 17, 2019

Great presentation of a variety of materials. There could have been some more details in terms of fully understanding some of the details, calculations, etc. You see this in the comments where folks struggle to be sure how the calculations are made. So that takes time and maybe the book as some of that. But all in all, just a great way to get introduced to some exciting work being done leveraging graphs.

創建者 HEF

•Apr 15, 2019

Challenging but worthwhile. So amazing that it took me to analyse things from a completely new perspective. I felt much more sophisticated in modeling things like economics, sociology, politics and epidemics, just to name a few. The course is well organized from simple basics in the first few weeks to the more advanced models in the later half. The quiz style is also very friendly to help me review the important concepts, and also try out softwares like Gephi and Pajek.

創建者 Michael S

•Jan 24, 2019

I loved everything so far, the quiz questions are well selected, but, I believe there are some notions which should be explained further mathematically.

創建者 kazuyuki h

•Dec 27, 2018

This lecture is a Great Introduction to Economic Networks.

Good point 1, many applications to economics research.

Good point 2, nice intuitive explanation to the notion of networks.

Note that MIT open course about Network can be complementary to this lecture.

創建者 Sebastián F

•Dec 22, 2018

Very nice and useful course.

創建者 Justin K

•Dec 10, 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.

創建者 Rijul K

•Dec 03, 2018

greaaaat course

創建者 Taras Z

•Dec 02, 2018

Good introduction to the topic! Assignments were helpful as well as optional lecture videos.

創建者 Noah J W

•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.

創建者 Yadnesh S

•Nov 04, 2018

Provides an in depth knowlledge about topics.

創建者 Emil

•Oct 27, 2018

Without previous knowledge in math, this course is not very useful.

創建者 Margarita R C G

•Oct 18, 2018

Great course! Teacher gave very good explanations. Examples are very useful. I would love to take a more advanced course of social and economic networks.

創建者 Ignacio O

•Oct 04, 2018

Awesome course with lots of applications!

創建者 Mansimran S A

•Oct 01, 2018

a very good excellent on social network analysis

創建者 Paolo B

•Sep 30, 2018

Excellent Course! Clear videos with many motivated problem sets. The advanced problem sets are exactly like university problem sets. Do be aware that sometimes parts of proofs are omitted or only touched on briefly to get to the main teaching points - these moments are made clear in lectures. While I enjoyed the practical exercises I did feel that extensions to these exercises are warranted.

創建者 pranav n

•Sep 05, 2018

needs more practical exercises

創建者 Yuze J

•Aug 28, 2018

The topic is quite interesting and Professor explains the concepts and theories in a quite understandable way. It is easy to follow the contents and offers me with a basic idea of the modeling of network effect. A very help course and highly recommend!

創建者 Krista M

•Aug 21, 2018

The chemistry disciplinary knowledge cautions the utilization of the idea of diffusion because diffusion in chemistry is more of systematic random process then the idea of diffusion in this lecture. If you could enhance and clarify the Week 4 lecture of the Praeto Efficiency, Utility, and Pairwise in additional examples the brevity of the lecture could build the idea into a few slides to sharpen the idea earlier. Think about adding more examples of the Centrality examples, I thought the Centrality was interesting.

創建者 Alejandro A R

•Jul 15, 2018

Greatly insightful and resourceful content for future research. As a recent university graduate interested in graduate school I found the course challenging meaning determination and consistency contributed to the successful completion of the course. Rewatching lectures and seeking external support helped me comprehend concepts through application.

創建者 David C

•Jul 12, 2018

Very interesting and applicable subject matter taught in a very engaging way. Prof. O'Jackson is clearly incredibly capable in network analysis and game theory and he teaches the concepts in a remarkably concise and understandable manner.

創建者 jaderne H

•Jul 09, 2018

Very interesting and well presented course .

創建者 Omar J

•Jul 07, 2018

An excellent walkthrough of the literature. I just wish there were more empirical exercises and and more hands-on work with the data and algorithms.

創建者 Michael G

•Apr 17, 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.

創建者 Laurent G

•Mar 01, 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.