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Retour à Réseaux sociaux et économiques : modèles et analyse

Avis et commentaires pour d'étudiants pour Réseaux sociaux et économiques : modèles et analyse par Université de Stanford

556 évaluations
118 avis

À propos du cours

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: You can find a short introductory videao here:

Meilleurs avis


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.

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76 - 100 sur 114 Avis pour Réseaux sociaux et économiques : modèles et analyse

par Ignacio O

Oct 04, 2018

Awesome course with lots of applications!

par Carlos J D

Aug 16, 2016

Nice course, well paced, great teacher!

par Moreno M

Dec 29, 2019

Great Professor, enlightening course!


Jan 22, 2017

Fantastic and interesting course.

par Ayushi R

May 30, 2020

Great Course. I learned a lot.

par pranav n

Sep 05, 2018

needs more practical exercises

par Sebastián F

Dec 22, 2018

Very nice and useful course.


Jul 01, 2020

I am enjoying the course

par Sourav M

May 24, 2020

Great course..!!

par John B

Sep 10, 2017

Wonderful course

par Rijul K

Dec 03, 2018

greaaaat course

par Богдан

Nov 25, 2016

Very intresting

par Anand R

Apr 27, 2020

Great Course!

par Mojtaba A

Oct 27, 2017

Great teacher

par Pablo E

Feb 12, 2018


par Hakobyan Z

Oct 20, 2017


par swapnil s

Oct 12, 2016


par Andy P

Oct 18, 2016


par anuj

May 30, 2017


par Stylianos T

Feb 24, 2017

A very good introduction in social and economic networks.

I recommend this course to everyone that wants to learn how networks are formed, understand the basic concepts and get an intuition on the possible networks that he/she could form.

The professor is talking clearly so you won't have a problem in understanding him.

One thing that was missing for me was in Week 2 when he was talking about "eigenvector centrality", for me the most objective measure, the explanation was really poor and you could never understand the concept based on what the lesson offered.

par KM

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.

par Carlson O

Apr 22, 2017

Very comprehensive as an introductory course. The content is very actual and the lectures' flow is objective. Also, I liked the quiz inside the lectures as they helped in retain the subject. I have some hard difficulties with the mathematics as I'm very rusty with the mathematics (more than 30 years of rust). I'm from the compute science area so I would like to see more practice in algorithms. However, I would like to congratulate the Stanford University and Cousera teams for the course. Great job.

par Fernando I P M

Aug 03, 2020

Buen curso en general. Sin embargo, podría estar más actualizado en términos de aplicaciones para el año 2020. Especialmente en trabajo con datos. Además, algunas evaluaciones adolecen de elementos que no están contenidos en el material, y si bien uno puede intuir a aplicar la teoría bajo otros contextos, muchas veces los resultados no son tan intuitivos, quedando algunas dudas respecto a esos contenidos más que clarificar dicho tópico.

par 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.

par GIAN M

May 04, 2020

Very interesting course, I raccomand it. It gives me a lot of notions and different view of networks, even if I'm already working with them. Very notable also the lot of references by which you can expand your knowledge and look for all the details of the field you are interested in.

Keep attention on the level, it is not for beginners :)