Social and Economic Networks: Models and Analysis(으)로 돌아가기

4.8

437개의 평가

•

90개의 리뷰

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.

필터링 기준:

교육 기관: Ajinkya K

•Oct 24, 2017

A great course for anyone interested in learning about networks and social interactions. This course is ideal for a wide range of audience, from someone looking for an overview and introduction to networks to someone looking for a deep dive into networks and applying it to their research. Matt is a great communicator and presents the ideas in an intuitive fashion , had a great time doing all his material. Thank you Stanford and Matt Jackson for this amazing experience.

교육 기관: Benjamin K

•May 20, 2017

Though this course confused the heck out of me many times, I have a broad understandings of what networks are and how they can be analyzed and modeled despite enrolling with minimal prior knowledge. I recommend it to anyone interested in analyzing how societies and their members behave and that when it seems difficult you stick it out. Thank you Matthew Jackson!

교육 기관: THANACHON C

•Apr 30, 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.

교육 기관: 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.

교육 기관: Abel V

•Jan 23, 2018

Excelente curso, con un muy buen balance entre la teoría y la aplicación.

교육 기관: 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.

교육 기관: Bei C

•Nov 30, 2017

Thank you Professor, your course is extremely useful for my research work in Social Network.

교육 기관: Pablo E

•Feb 12, 2018

Excellent

교육 기관: Jess B

•Jul 14, 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.

교육 기관: ANTONINO A

•Jan 22, 2017

Fantastic and interesting course.

교육 기관: 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.

교육 기관: Alejandro M M

•May 30, 2017

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.

교육 기관: Mikhail K

•Nov 26, 2017

Extremely interesting and very well presented course. Many thanks to Matthew!!!

교육 기관: Mojtaba A

•Oct 27, 2017

Great teacher

교육 기관: Cailean O

•Jan 30, 2018

Professor Jackson explains the concepts very clearly; great course. Thank you!

교육 기관: anuj

•May 30, 2017

best

교육 기관: 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.

교육 기관: 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.

교육 기관: 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

교육 기관: Gubanov A

•Jul 03, 2019

The course is very useful. The teacher is great also, thank's a lot.

교육 기관: Manuel S

•Jul 09, 2019

Excellent introduction to the world of networks. The course covers the basics in a clear and organized manner. I highly recommend it, and after that you are ready to read the literature of the area. Thank you, very much, Professor Jackson.

교육 기관: Herbaut J P M

•Jul 16, 2019

Excellent expérience ! Thanks You.

Herbaut Julien

교육 기관: 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.

교육 기관: 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.

교육 기관: 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.