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Social and Economic Networks: Models and Analysis(으)로 돌아가기

스탠퍼드 대학교의 Social and Economic Networks: Models and Analysis 학습자 리뷰 및 피드백

4.8
454개의 평가
93개의 리뷰

강좌 소개

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...

최상위 리뷰

MR

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 :)

SW

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.

필터링 기준:

Social and Economic Networks: Models and Analysis의 90개 리뷰 중 76~90

교육 기관: Justin K

Dec 10, 2018

Excellent course. The labs are the best. Pajek and Gephi will be handy for network graphing and analyzing data. Thank you Professor Matthew Jackson. Your work is very good for reference.

교육 기관: Michael S

Jan 24, 2019

I loved everything so far, the quiz questions are well selected, but, I believe there are some notions which should be explained further mathematically.

교육 기관: Krista M

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.

교육 기관: 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.

교육 기관: Navin N

Dec 10, 2016

A bit tough, but really worth the effort.

교육 기관: Tianduo Z

Nov 02, 2016

Very complex topic, very well presented. The materials are great! Would have been better to made mathematics pre-requisite clearer.

교육 기관: Harkeerat S T

Dec 22, 2016

The course is vast. The Professor is to the point and doesn't lack knowledge in his field.

I'd recommend this course for anyone interested in Economics. Loved it.

교육 기관: 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.

교육 기관: Dheeraj B

Oct 04, 2017

The discussion forums ought to be more responsive

교육 기관: Felipe O G C B

Aug 25, 2016

It's a quiet complex topic in general terms. It is well covered, but In my opinion there should be at least an exercise per video, explaining something similar to the in-video questions. It should have a demonstrative part rather than just talking about it and showing the formula.

교육 기관: 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.

교육 기관: Jose

Jan 23, 2018

This course is very good to introduce to the theory of networks

교육 기관: Sebastian H

Oct 15, 2019

Hohes Anforderungsniveau, mathematische Fähigkeiten sind zwingend erforderlich.

교육 기관: Muhammad I

Oct 10, 2017

I'm sorry, but this course is really boring. Hopefully this lecture give more interactive approach (like animated presentation, pop up question, and so on) rather than voice of text in the slide

교육 기관: Emil

Oct 27, 2018

Without previous knowledge in math, this course is not very useful.