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Learner Reviews & Feedback for Social and Economic Networks: Models and Analysis by Stanford University

4.8
stars
749 ratings

About the Course

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...

Top reviews

MR

Nov 2, 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 :)

SB

Oct 11, 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.

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126 - 150 of 174 Reviews for Social and Economic Networks: Models and Analysis

By Rafael S

•

Nov 29, 2023

Very interesting.

By Gustavo S

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Jun 6, 2023

Very good course!

By Sourav M

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May 24, 2020

Great course..!!

By John B

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Sep 10, 2017

Wonderful course

By Phan T B T T

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Jun 1, 2021

Great course!!1

By Raya R D

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Dec 3, 2018

greaaaat course

By Богдан

•

Nov 25, 2016

Very intresting

By Adil M

•

Oct 27, 2024

Brilliant!!!!

By Anand A R

•

Apr 27, 2020

Great Course!

By Mojtaba A

•

Oct 27, 2017

Great teacher

By patrick

•

Aug 15, 2022

good course

By Antonio C

•

Oct 14, 2020

big course

By Christiano F d C

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Oct 4, 2020

Very good!

By Mohammad N C

•

Mar 17, 2021

Excellent

By Pablo E

•

Feb 12, 2018

Excellent

By Zaruhi H

•

Oct 20, 2017

Thanks!

By Swapnil S

•

Oct 12, 2016

Great!!

By José V

•

Jun 28, 2024

Great!

By Keshore P

•

May 25, 2023

Greats

By Andy P

•

Oct 18, 2016

great!

By anuj

•

May 30, 2017

best

By tanghaolin

•

Oct 11, 2023

666

By David S

•

Aug 4, 2022

This is a fascinating and stimulating course in which I learned enough to make my brain overheat at the end of every session. It's heavy for the non-mathmetician, but you just have to struggle to keep up when the going gets numerically tough. My one gripe is that it leans too far towards formulas, and not enough to real-world examples and application. For example, in Week 6 admist the equations, there was suddenly a look at how it applies to drop-out rates in the labour market. That was all too brief, and more of this would really lift the course. Jackson really knows his onions however and is an interesting and sympathetic tutor.

By Stylianos T

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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.

By Krista M

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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.