Chevron Left
Voltar para Redes Sociais e Econômicas: Modelos e Análises

Comentários e feedback de alunos de Redes Sociais e Econômicas: Modelos e Análises da instituição Universidade de Stanford

4.8
estrelas
653 classificações
149 avaliações

Sobre o 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: 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...

Melhores avaliações

LN
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.

AB
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!!!

Filtrar por:

101 — 125 de 145 Avaliações para o Redes Sociais e Econômicas: Modelos e Análises

por ANTONINO A

22 de Jan de 2017

Fantastic and interesting course.

por Ayushi R

30 de Mai de 2020

Great Course. I learned a lot.

por pranav n

5 de Set de 2018

needs more practical exercises

por Sebastián F

22 de Dez de 2018

Very nice and useful course.

por CHARLOTTE P

1 de Jul de 2020

I am enjoying the course

por Sourav M

24 de Mai de 2020

Great course..!!

por John B

10 de Set de 2017

Wonderful course

por Phan T B T

31 de Mai de 2021

Great course!!1

por Rijul K

3 de Dez 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 Out de 2017

Great teacher

por Antonio C

14 de Out de 2020

big course

por Christiano F d C

4 de Out de 2020

Very good!

por Mohammad N C

17 de Mar de 2021

Excellent

por Pablo E

12 de Fev de 2018

Excellent

por Zaruhi H

20 de Out de 2017

Thanks!

por swapnil s

12 de Out de 2016

Great!!

por Andy P

18 de Out de 2016

great!

por anuj

30 de Mai de 2017

best

por Stylianos T

24 de Fev 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.

por Fernando I P M

3 de Ago de 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.

por Alejandro A R

15 de Jul de 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.