課程信息
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高級

完成時間大約為25 小時

英語(English)

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Social NetworkGame TheoryNetwork AnalysisNetwork Theory

100% 在線

立即開始,按照自己的計劃學習。

可靈活調整截止日期

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高級

完成時間大約為25 小時

英語(English)

字幕:英語(English)

教學大綱 - 您將從這門課程中學到什麼

1
完成時間為 3 小時

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

...
12 個視頻 (總計 118 分鐘), 3 個閱讀材料, 3 個測驗
12 個視頻
1.1: Introduction9分鐘
1.2: Examples and Challenges 15分鐘
1.2.5 Background Definitions and Notation (Basic - Skip if familiar 8:23)8分鐘
1.3: Definitions and Notation 14分鐘
1.4: Diameter 16分鐘
1.5: Diameter and Trees 6分鐘
1.6: Diameters of Random Graphs (Optional/Advanced 11:12)11分鐘
1.7: Diameters in the World 6分鐘
1.8: Degree Distributions 13分鐘
1.9: Clustering 8分鐘
1.10: Week 1 Wrap2分鐘
3 個閱讀材料
Syllabus10分鐘
Slides from Lecture 1, with References10分鐘
OPTIONAL - Advanced Problem Set 110分鐘
3 個練習
Quiz Week 128分鐘
Problem Set 112分鐘
Optional: Empirical Analysis of Network Data using Gephi or Pajek8分鐘
2
完成時間為 3 小時

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

...
11 個視頻 (總計 105 分鐘), 3 個閱讀材料, 3 個測驗
11 個視頻
2.2: Dynamics and Tie Strength 6分鐘
2.3: Centrality Measures 14分鐘
2.4: Centrality – Eigenvector Measures 13分鐘
2.5a: Application - Centrality Measures 12分鐘
2.5b: Application – Diffusion Centrality 6分鐘
2.6: Random Networks 10分鐘
2.7: Random Networks - Thresholds and Phase Transitions 7分鐘
2.8: A Threshold Theorem (optional/advanced 13:00)13分鐘
2.9: A Small World Model 7分鐘
2.10 Week 2 Wrap3分鐘
3 個閱讀材料
Slides from Lecture 2, with references10分鐘
OPTIONAL - Advanced Problem Set 210分鐘
OPTIONAL - Solutions to Advanced PS 110分鐘
3 個練習
Quiz Week 216分鐘
Problem Set 210分鐘
Optional: Empirical Analysis of Network Data6分鐘
3
完成時間為 4 小時

Random Networks

Poisson Random Networks, Exponential Random Graph Models, Growing Random Networks, Preferential Attachment and Power Laws, Hybrid models of Network Formation.

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12 個視頻 (總計 143 分鐘), 3 個閱讀材料, 4 個測驗
12 個視頻
3.2: Mean Field Approximations 8分鐘
3.3: Preferential Attachment 10分鐘
3.4: Hybrid Models 14分鐘
3.5: Fitting Hybrid Models 17分鐘
3.6: Block Models 9分鐘
3.7: ERGMs 9分鐘
3.8: Estimating ERGMs 15分鐘
3.9: SERGMs 9分鐘
3.10: SUGMs 6分鐘
3.11: Estimating SUGMs (Optional/Advanced 21:03)21分鐘
3.12: Week 3 Wrap3分鐘
3 個閱讀材料
Slides from Lecture 3, with references10分鐘
OPTIONAL - Advanced Problem Set 310分鐘
OPTIONAL - Solutions to Advanced PS 210分鐘
4 個練習
Quiz Week 326分鐘
Problem Set 36分鐘
Optional: Empirical Analysis of Network Data4分鐘
Optional: Using Statnet in R to Estimate an ERGM6分鐘
4
完成時間為 5 小時

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.

...
15 個視頻 (總計 209 分鐘), 3 個閱讀材料, 2 個測驗
15 個視頻
4.2: Pairwise Stability and Efficiency 15分鐘
4.3: Connections Model 11分鐘
4.4: Efficiency in the Connections Model (Optional/Advanced 12:41)12分鐘
4.5: Pairwise Stability in the Connections Model 6分鐘
4.6: Externalities and the Coauthor Model 11分鐘
4.7: Network Formation and Transfers 16分鐘
4.8: Heterogeneity in Strategic Models 13分鐘
4.9: SUGMs and Strategic Network Formation (Optional/Advanced 13:47)13分鐘
4.10: Pairwise Nash Stability (Optional/Advanced 11:34)11分鐘
4.11: Dynamic Strategic Network Formation (Optional/Advanced 11:57)11分鐘
4.12: Evolution and Stochastics (Optinoal/Advanced 16:05)16分鐘
4.13: Directed Network Formation (Optional/Advanced 16:38)16分鐘
4.14: Application Structural Model (Optional/Advanced 35:06)35分鐘
4.15: Week 4 Wrap4分鐘
3 個閱讀材料
Slides from Lecture 4, with references10分鐘
OPTIONAL - Advanced Problem Set 410分鐘
OPTIONAL - Solutions to Advanced PS 310分鐘
2 個練習
Quiz Week 436分鐘
Problem Set 414分鐘
4.8
87 個審閱Chevron Right

來自社会和经济网络:模型和分析的熱門評論

創建者 MRNov 2nd 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 :)

創建者 SWAug 9th 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.

講師

Avatar

Matthew O. Jackson

Professor
Economics

關於 斯坦福大学

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....

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