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.
제공자:
Social and Economic Networks: Models and Analysis
스탠퍼드 대학교
About this Course
최근 조회 61,766회
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귀하가 습득할 기술
Social NetworkGame TheoryNetwork AnalysisNetwork Theory
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지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
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일정에 따라 마감일을 재설정합니다.
고급 단계
완료하는 데 약 25시간 필요
영어
자막: 영어
제공자:
스탠퍼드 대학교
The Leland Stanford Junior University, commonly referred to as Stanford University or Stanford, is an American private research university located in Stanford, California on an 8,180-acre (3,310 ha) campus near Palo Alto, California, United States.
강의 계획 - 이 강좌에서 배울 내용
완료하는 데 3시간 필요
Introduction, Empirical Background and Definitions
Examples of Social Networks and their Impact, Definitions, Measures and Properties: Degrees, Diameters, Small Worlds, Weak and Strong Ties, Degree Distributions
완료하는 데 3시간 필요
12개 동영상 (총 118분), 3 readings, 3 quizzes
12개의 동영상
1.1: Introduction9m
1.2: Examples and Challenges 15m
1.2.5 Background Definitions and Notation (Basic - Skip if familiar 8:23)8m
1.3: Definitions and Notation 14m
1.4: Diameter 16m
1.5: Diameter and Trees 6m
1.6: Diameters of Random Graphs (Optional/Advanced 11:12)11m
1.7: Diameters in the World 6m
1.8: Degree Distributions 13m
1.9: Clustering 8m
1.10: Week 1 Wrap2m
3개의 읽기 자료
Syllabus10m
Slides from Lecture 1, with References10m
OPTIONAL - Advanced Problem Set 110m
3개 연습문제
Quiz Week 128m
Problem Set 112m
Optional: Empirical Analysis of Network Data using Gephi or Pajek8m
완료하는 데 3시간 필요
Background, Definitions, and Measures Continued
Homophily, Dynamics, Centrality Measures: Degree, Betweenness, Closeness, Eigenvector, and Katz-Bonacich. Erdos and Renyi Random Networks: Thresholds and Phase Transitions
완료하는 데 3시간 필요
11개 동영상 (총 105분), 3 readings, 3 quizzes
11개의 동영상
2.2: Dynamics and Tie Strength 6m
2.3: Centrality Measures 14m
2.4: Centrality – Eigenvector Measures 13m
2.5a: Application - Centrality Measures 12m
2.5b: Application – Diffusion Centrality 6m
2.6: Random Networks 10m
2.7: Random Networks - Thresholds and Phase Transitions 7m
2.8: A Threshold Theorem (optional/advanced 13:00)13m
2.9: A Small World Model 7m
2.10 Week 2 Wrap3m
3개의 읽기 자료
Slides from Lecture 2, with references10m
OPTIONAL - Advanced Problem Set 210m
OPTIONAL - Solutions to Advanced PS 110m
3개 연습문제
Quiz Week 216m
Problem Set 210m
Optional: Empirical Analysis of Network Data6m
완료하는 데 4시간 필요
Random Networks
Poisson Random Networks, Exponential Random Graph Models, Growing Random Networks, Preferential Attachment and Power Laws, Hybrid models of Network Formation.
완료하는 데 4시간 필요
12개 동영상 (총 143분), 3 readings, 4 quizzes
12개의 동영상
3.2: Mean Field Approximations 8m
3.3: Preferential Attachment 10m
3.4: Hybrid Models 14m
3.5: Fitting Hybrid Models 17m
3.6: Block Models 9m
3.7: ERGMs 9m
3.8: Estimating ERGMs 15m
3.9: SERGMs 9m
3.10: SUGMs 6m
3.11: Estimating SUGMs (Optional/Advanced 21:03)21m
3.12: Week 3 Wrap3m
3개의 읽기 자료
Slides from Lecture 3, with references10m
OPTIONAL - Advanced Problem Set 310m
OPTIONAL - Solutions to Advanced PS 210m
4개 연습문제
Quiz Week 326m
Problem Set 36m
Optional: Empirical Analysis of Network Data4m
Optional: Using Statnet in R to Estimate an ERGM6m
완료하는 데 5시간 필요
Strategic Network Formation
Game Theoretic Modeling of Network Formation, The Connections Model, The Conflict between Incentives and Efficiency, Dynamics, Directed Networks, Hybrid Models of Choice and Chance.
완료하는 데 5시간 필요
15개 동영상 (총 209분), 3 readings, 2 quizzes
15개의 동영상
4.2: Pairwise Stability and Efficiency 15m
4.3: Connections Model 11m
4.4: Efficiency in the Connections Model (Optional/Advanced 12:41)12m
4.5: Pairwise Stability in the Connections Model 6m
4.6: Externalities and the Coauthor Model 11m
4.7: Network Formation and Transfers 16m
4.8: Heterogeneity in Strategic Models 13m
4.9: SUGMs and Strategic Network Formation (Optional/Advanced 13:47)13m
4.10: Pairwise Nash Stability (Optional/Advanced 11:34)11m
4.11: Dynamic Strategic Network Formation (Optional/Advanced 11:57)11m
4.12: Evolution and Stochastics (Optinoal/Advanced 16:05)16m
4.13: Directed Network Formation (Optional/Advanced 16:38)16m
4.14: Application Structural Model (Optional/Advanced 35:06)35m
4.15: Week 4 Wrap4m
3개의 읽기 자료
Slides from Lecture 4, with references10m
OPTIONAL - Advanced Problem Set 410m
OPTIONAL - Solutions to Advanced PS 310m
2개 연습문제
Quiz Week 436m
Problem Set 414m
검토
4.8
SOCIAL AND ECONOMIC NETWORKS: MODELS AND ANALYSIS의 최상위 리뷰
MR 제공Nov 1, 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 제공Aug 8, 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.
JK 제공Dec 9, 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.
MG 제공Apr 16, 2018
Great survey course for social network analysis. Dr. Jackson's lectures motivated me to buy the book, and I hope to come back to this course later to work more on the optional parts.
TC 제공Apr 29, 2017
An overview of concepts and models of how networks form. There are applicable with basic concepts from probability theory, statistics, and some light calculus astonishingly well.
HT 제공Dec 21, 2016
The course is vast. The Professor is to the point and doesn't lack knowledge in his field.\n\nI'd recommend this course for anyone interested in Economics. Loved it.
AC 제공Sep 3, 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.
OJ 제공Jul 6, 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.
GP 제공Jun 24, 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
EA 제공May 14, 2017
Fantastic course! Compelling examples of application and an enthusiasm for the concepts that is contagious. Would love more from Prof. Jackson!
CT 제공Feb 2, 2020
Professor Jackson is very clear and insightful! Loved his style of teaching. I hope more Economics professors were such good teachers as him.
PV 제공Jun 20, 2017
An excellent and very useful course. Recommend with no reserves to anyone willing to understand the world from a well structured perspective
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