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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
별점
546개의 평가
117개의 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 113개 리뷰 중 26~50

교육 기관: Digant S

Jun 14, 2017

This course is quite helpful as network theory can be applied in epidemiology, economics, sociology and even physics. I would recommend this to anyone who wishes to learn how a certain group of subjects act in real world situations.

교육 기관: zuselcursos

Nov 20, 2017

This course is amazing, worth it a lot, I learned about game theory, mathematics, sociology. The teacher is very patient , I liked the practice test on Gelphi and the mathematical background in addition real life applications.

교육 기관: Vikram D K

Apr 24, 2017

Lucidly taught by Prof. Jackson. I learned a whole deal of stuff that helps me make sense of some of the literature in economics that uses ideas from network analysis. My background is in economics (Master's degree).

교육 기관: david l

Nov 03, 2017

Really interesting. there is a lot of material and a lot of formula to be covered and Prof. Jackson does a great job teaching it.

Also, his book is really intesresting and goest deeper than the videoes

교육 기관: Manoel H R

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 :)

교육 기관: Siqi, W

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.

교육 기관: Moritz P

May 17, 2020

Matt is a fantastic instructor and has inspired many new ideas for my PhD project. Putting this course up here for free is extremely generous of both Matt and Coursera.

교육 기관: Avi C

Sep 04, 2016

The course is a helpful first step in the field of network science. Presenting clearly many complex ideas that are important for understanding current research.

교육 기관: Margarita R C G

Oct 18, 2018

Great course! Teacher gave very good explanations. Examples are very useful. I would love to take a more advanced course of social and economic networks.

교육 기관: Omar J

Jul 07, 2018

An excellent walkthrough of the literature. I just wish there were more empirical exercises and and more hands-on work with the data and algorithms.

교육 기관: Gabriel P

Jun 25, 2016

A very usefull course very different from others. Although for coursera standars, its very extensive and not so basic, that´s why I think its great

교육 기관: Erikson A

May 15, 2017

Fantastic course! Compelling examples of application and an enthusiasm for the concepts that is contagious. Would love more from Prof. Jackson!

교육 기관: Carlos A N T

Feb 03, 2020

Professor Jackson is very clear and insightful! Loved his style of teaching. I hope more Economics professors were such good teachers as him.

교육 기관: Aron D H

Jun 08, 2020

The course is extremely interesting and well presented. It is a great introduction to network science with various examples of applications.

교육 기관: Prohnițchi V

Jun 21, 2017

An excellent and very useful course. Recommend with no reserves to anyone willing to understand the world from a well structured perspective

교육 기관: Alejandro M M

May 30, 2017

Matt is the simple the best! We've covered a lot of different models and examples. Probably the best networks course that you can take.

교육 기관: Marco R

Feb 22, 2020

Useful, well taught, well organized. I suppose the coronavirus epidemic gives an opportunity for a real world example next year

교육 기관: 李楠楠

Feb 13, 2017

Easier to understand network structure, utilities, equilibrium after illustration. Interesting and attracting course to take.

교육 기관: Amirhessam Y

Oct 31, 2016

The course is exceptional, I just wish the instructor would also include chapters that could help researchers in the field.

교육 기관: Ali K

Feb 05, 2020

It was really useful. The instructor was clear and the videos and slides are good. I enjoyed empirical exercise a lot.

교육 기관: anubhav g

Aug 12, 2016

A great course which gives an overall idea regarding the tools required to study networks and its applications.

교육 기관: Nidhi S

Oct 08, 2016

A beautiful course that is mathematically rigorous and requires great understanding. Thank you :)

교육 기관: Taras Z

Dec 02, 2018

Good introduction to the topic! Assignments were helpful as well as optional lecture videos.

교육 기관: Bei C

Nov 30, 2017

Thank you Professor, your course is extremely useful for my research work in Social Network.

교육 기관: Sihua D

Sep 18, 2016

Great course by Matt Jackson, who is one of the leading scholars in this area! Thanks!