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Social and Economic Networks: Models and Analysis に戻る

スタンフォード大学(Stanford University) による Social and Economic Networks: Models and Analysis の受講者のレビューおよびフィードバック

4.8
679件の評価

コースについて

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...

人気のレビュー

AB

2021年4月21日

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!!!

LN

2021年7月2日

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.

フィルター:

Social and Economic Networks: Models and Analysis: 126 - 150 / 151 レビュー

by David S

2022年8月4日

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

2017年2月24日

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

2018年8月21日

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.

by Carlson O

2017年4月22日

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.

by Fernando I P M

2020年8月3日

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.

by Alejandro A R

2018年7月15日

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.

by Gian M C

2020年5月4日

Very interesting course, I raccomand it. It gives me a lot of notions and different view of networks, even if I'm already working with them. Very notable also the lot of references by which you can expand your knowledge and look for all the details of the field you are interested in.

Keep attention on the level, it is not for beginners :)

by Felipe O G C B

2016年8月25日

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.

by Mateus d C C

2021年1月19日

Great course, a bit complicated sometimes. The course is very structured and the classes are ordered is a natural way. The tests weren't hard and I think the course could focus more on experimental exercises.

by Justin K

2018年12月10日

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.

by Simon N

2020年6月6日

Interesting survey of modern network theory, from Erdos-Renyi random graphs, to SIS ("flu") models, and games on networks. Rather academic at times, without the rigour.

by Harkeerat S

2016年12月22日

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.

by Michael S

2019年1月24日

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

by Tianduo Z

2016年11月1日

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

by Robertas K

2020年5月31日

Some quizzes have wrong answers, but overall it was quite a good introduction into network analysis.

by ND B

2020年9月17日

I request Prof Jackson to speak more directly into the mike. At many points he is not audible.

by Pedro G

2021年7月2日

Some modules were really useful to create solutions for my professional challenges.

by Sebastian H

2019年10月15日

Hohes Anforderungsniveau, mathematische Fähigkeiten sind zwingend erforderlich.

by Jose

2018年1月23日

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

by XeRh

2020年8月8日

It's very useful if you want to learn more anout network.

by Dheeraj B

2017年10月4日

The discussion forums ought to be more responsive

by Navin N

2016年12月10日

A bit tough, but really worth the effort.

by Muhammad I

2017年10月10日

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

by ssagnik s

2021年2月1日

the content is good but without basic knowledge of network, it will difficult to understand

the narrator is extremely boring and the explanation is not clear at all.

I expect to learn something new but it bored me

by Alexandra M

2020年9月9日

hola! me gustaría darme de baja de este curso. NO fue una buena elección.