Retour à Réseaux sociaux et économiques : modèles et analyse

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150 avis

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...

AB

21 avr. 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!!!

LN

2 juil. 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.

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par Michael G

•16 avr. 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.

par Isard D

•15 mai 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

par THANACHON C

•29 avr. 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.

par Nikita S

•29 mai 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.

par Sanjoy B

•11 oct. 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.

par Siqi, W

•8 août 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.

par Laurent G

•1 mars 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.

par Tongtong H

•5 déc. 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!

par Julia L B

•18 avr. 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.

par DoubleJ J

•13 juil. 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.

par Raphael M F

•3 mars 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.

par Rebecca A

•13 janv. 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.

par HEF

•15 avr. 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.

par Ajinkya K

•24 oct. 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.

par Llewellyn P

•17 avr. 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.

par Noah J W

•17 nov. 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.

par Paolo B

•30 sept. 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.

par EKATERINA A

•25 nov. 2019

Excellent course! The course exceeded my expectations. It takes you beyond the basics of social network analysis, but does it very gently. I enjoyed the content, the way it is given, the variety of levels on which you could stay while studying (from absolute beginner to rather advanced learner) and the teacher's expertise (as well as his sense of humor). Thank you, Matt!!!

par Prokopis G

•18 sept. 2016

Excellent course. The material is very well presented. You get the chance to understand the intuitions behind many concepts relating to SNA in a very systematic manner. Can serve as a good basis for M.Sc or Phd level students that are interested to explore this area. The evaluation process is really well defined and the length of course is really appropriate.

Thanks,

Prokopis

par Ana T M

•8 sept. 2020

Very interesting topic, important to wide range of disciplines and I believes that it pays off to go into this subjects (at least to gain more insight on ways in which our connected world functions). Course contains some complex issues but they are explained in such understandable way - I appreciate the effort of prof. Jackson very much. I enjoy learning with this course.

par Benjamin K

•19 mai 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!

par Haoran Y

•16 mars 2021

This is a very good course designed for both beginners and advanced learners of Network analysis. The assignments have been divided into both standard and advanced tasks so that to meet different needs. The organization of it is clear and reasonable. I will recommend everyone who is interested or curious about network analysis to start learning this course!

par Chao W

•3 janv. 2022

The course is super interesting and very well structured. The lengths of videos fit the learner's attention span well. The quizzes during lectures keep learners engaged. Problem sets are very useful tools for reviewing. In all, a big thank you to Prof. Jackson for a wonderful learning experience.

par Paul R

•6 nov. 2016

Great course!

It's a theoretical course and it's definitely harder than many of the other courses offered on Coursera. The quizzes and final exam are definitely doable but understanding everything perfectly is not an easy task. The professor is very clear. I highly recommend this course.

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