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Volver a Social and Economic Networks: Models and Analysis

Opiniones y comentarios de aprendices correspondientes a Social and Economic Networks: Models and Analysis por parte de Universidad de Stanford

670 calificaciones
151 reseña

Acerca del Curso

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:

Principales reseñas


2 de jul. de 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.


21 de abr. de 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!!!

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101 - 125 de 147 revisiones para Social and Economic Networks: Models and Analysis

por Moreno M

29 de dic. de 2019

Great Professor, enlightening course!

por Andre S

16 de feb. de 2021

Excellent course! Very didactic!!!!


22 de ene. de 2017

Fantastic and interesting course.

por Ayushi R

30 de may. de 2020

Great Course. I learned a lot.

por pranav n

5 de sep. de 2018

needs more practical exercises

por Sebastián F

22 de dic. de 2018

Very nice and useful course.


1 de jul. de 2020

I am enjoying the course

por Sourav M

24 de may. de 2020

Great course..!!

por John B

10 de sep. de 2017

Wonderful course

por Phan T B T

31 de may. de 2021

Great course!!1

por Rijul K

3 de dic. de 2018

greaaaat course

por Богдан

25 de nov. de 2016

Very intresting

por Anand A R

27 de abr. de 2020

Great Course!

por Mojtaba A

27 de oct. de 2017

Great teacher

por Antonio C

14 de oct. de 2020

big course

por Christiano F d C

4 de oct. de 2020

Very good!

por Mohammad N C

17 de mar. de 2021


por Pablo E

12 de feb. de 2018


por Zaruhi H

20 de oct. de 2017


por swapnil s

12 de oct. de 2016


por Andy P

18 de oct. de 2016


por anuj

30 de may. de 2017


por Stylianos T

24 de feb. de 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.

por KM

21 de ago. de 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.

por Carlson O

22 de abr. de 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.