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Social and Economic Networks: Models and Analysis

Курс от Stanford Online
Продвинутый≈ 29.9 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

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

Навыки, которые вы освоите

Network AnalysisSocial Network AnalysisGame TheoryProbabilitySociologySocioeconomicsBayesian StatisticsSocial SciencesMathematical ModelingStatistical ModelingBehavioral Economics

Программа курса

8 модулей · 123 учебных материалов

01Introduction, Empirical Background and Definitions 18 материалов

Week 1: Introduction, Empirical Background and Definitions

An Introduction to the CourseВидеоSyllabusЧтение1.1: IntroductionВидео1.2: Examples and Challenges Видео

Учитесь у экспертов

Matthew O. Jackson

Professor

Social and Economic Networks:  Models and Analysis
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Обучение на Coursera

≈ 29.9 ч

8 модулей

Язык: Английский

Субтитры: Китайский (Тайвань), Арабский, Французский, Бенгальский, Узбекский, Украинский, Китайский (Китай), Греческий, Итальянский, Бразильский португальский, Вьетнамский, Нидерландский, Корейский, Немецкий, Пушту, Урду, Русский, Тайский, Индонезийский, Шведский, Турецкий, Азербайджанский, Испанский, Дари, Хинди, Японский, Финский, Казахский, Малайский, Венгерский, Польский

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1.2.5 Background Definitions and Notation (Basic - Skip if familiar 8:23)Видео
1.3: Definitions and Notation Видео
1.4: Diameter Видео
1.5: Diameter and Trees Видео
1.6: Diameters of Random Graphs (Optional/Advanced 11:12)Видео
1.7: Diameters in the World Видео
1.8: Degree Distributions Видео
1.9: Clustering Видео
1.10: Week 1 WrapВидео
Quiz Week 1Задание
Problem Set 1Задание
Optional: Empirical Analysis of Network Data using Gephi or PajekЗадание
Slides from Lecture 1, with ReferencesЧтение
OPTIONAL - Advanced Problem Set 1Чтение
02Background, Definitions, and Measures Continued17 материалов

Week 2: Background, Definitions, and Measures Continued

2.1: HomophilyВидео2.2: Dynamics and Tie Strength Видео2.3: Centrality Measures Видео2.4: Centrality – Eigenvector Measures Видео2.5a: Application - Centrality Measures Видео2.5b: Application – Diffusion Centrality Видео2.6: Random Networks Видео2.7: Random Networks - Thresholds and Phase Transitions Видео2.8: A Threshold Theorem (optional/advanced 13:00)Видео2.9: A Small World Model Видео2.10 Week 2 WrapВидеоQuiz Week 2ЗаданиеProblem Set 2ЗаданиеOptional: Empirical Analysis of Network DataЗаданиеSlides from Lecture 2, with referencesЧтениеOPTIONAL - Advanced Problem Set 2ЧтениеOPTIONAL - Solutions to Advanced PS 1Чтение
03Random Networks19 материалов

Week 3: Random Networks

3.1: Growing Random NetworksВидео3.2: Mean Field Approximations Видео3.3: Preferential Attachment Видео3.4: Hybrid Models Видео3.5: Fitting Hybrid Models Видео3.6: Block Models Видео3.7: ERGMs Видео3.8: Estimating ERGMs Видео3.9: SERGMs Видео3.10: SUGMs Видео3.11: Estimating SUGMs (Optional/Advanced 21:03)Видео3.12: Week 3 WrapВидеоQuiz Week 3ЗаданиеProblem Set 3ЗаданиеOptional: Empirical Analysis of Network DataЗаданиеOptional: Using Statnet in R to Estimate an ERGMЗаданиеSlides from Lecture 3, with referencesЧтениеOPTIONAL - Advanced Problem Set 3ЧтениеOPTIONAL - Solutions to Advanced PS 2Чтение
04Strategic Network Formation20 материалов

Week 4: Strategic Network Formation

4.1: Strategic Network FormationВидео4.2: Pairwise Stability and Efficiency Видео4.3: Connections Model Видео4.4: Efficiency in the Connections Model (Optional/Advanced 12:41)Видео4.5: Pairwise Stability in the Connections Model Видео4.6: Externalities and the Coauthor Model Видео4.7: Network Formation and Transfers Видео4.8: Heterogeneity in Strategic Models Видео4.9: SUGMs and Strategic Network Formation (Optional/Advanced 13:47)Видео4.10: Pairwise Nash Stability (Optional/Advanced 11:34)Видео4.11: Dynamic Strategic Network Formation (Optional/Advanced 11:57)Видео4.12: Evolution and Stochastics (Optinoal/Advanced 16:05)Видео4.13: Directed Network Formation (Optional/Advanced 16:38)Видео4.14: Application Structural Model (Optional/Advanced 35:06)Видео4.15: Week 4 WrapВидеоQuiz Week 4ЗаданиеProblem Set 4ЗаданиеSlides from Lecture 4, with referencesЧтениеOPTIONAL - Advanced Problem Set 4ЧтениеOPTIONAL - Solutions to Advanced PS 3Чтение
05Diffusion on Networks18 материалов

Week 5: Diffusion on Networks

5.1: DiffusionВидео5.2: Bass ModelВидео5.3: Diffusion on Random Networks Видео5.4: Giant Component Poisson Case Видео5.5: SIS ModelВидео5.6: Solving the SIS Model Видео5.7: Solving the SIS Model - Ordering (Optional/Advanced 24:16)Видео5.8a: Fitting a Diffusion Model to Data (Optional/Advanced 22:47)Видео5.8b: Application: Financial Contagions (Optional/Advanced 12:47)Видео5.8c: Application: Financial Contagions - Simulations (Optional/Advanced 13:41)Видео5.9: Diffusion Summary Видео5.10: Week 5 WrapВидеоQuiz Week 5ЗаданиеProblem Set 5ЗаданиеOptional: Empirical Analysis of Network DataЗаданиеOPTIONAL - Advanced Problem Set 5ЧтениеOPTIONAL - Solutions to Advanced PS 4ЧтениеSlides from Lecture 5, with referencesЧтение
06Learning on Networks14 материалов

Week 6: Learning on Networks

6.1: LearningВидео6.2: DeGroot Model Видео6.3: Convergence in DeGroot Model Видео6.4: Proof of Convergence Theorem (Optional/Advanced 10:25)Видео6.5: Influence Видео6.6: Examples of Influence Видео6.7: Information Aggregation Видео6.8: Learning Summary Видео6.9: Week 6 WrapВидеоQuiz Week 6ЗаданиеProblem Set 6ЗаданиеSlides from Lecture 6, with referencesЧтениеOPTIONAL - Advanced Problem Set 6ЧтениеOPTIONAL - Solutions to Advanced PS 5Чтение
07Games on Networks16 материалов

Week 7: Games on Networks

7.1: Games on NetworksВидео7.2: Complements and Substitutes Видео7.3: Properties of Equilibria Видео7.4: Multiple Equilibria Видео7.5: An Application Видео7.6: Beyond 0-1 Choices Видео7.7: A Linear Quadratic Model Видео7.8: RepeatedGames and Networks Видео7.9: Week 7 Wrap Видео7.9b: Course WrapВидеоQuiz Week 7ЗаданиеProblem Set 7ЗаданиеSlides from Lecture 7, with referencesЧтениеOPTIONAL - Advanced Problem Set 7ЧтениеOPTIONAL - Solutions to Advanced PS 6ЧтениеOPTIONAL - Solutions to Advanced PS 7Чтение
08Final Exam1 материалов

Week 8: Final Exam

FinalЗадание