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コース：Social and Economic Networks: Models and Analysis戻るには、こちら をクリックしてください。
- An Introduction to the Course
- 1.1: Introduction
- 1.2: Examples and Challenges
- 1.2.5 Background Definitions and Notation (Basic - Skip if familiar 8:23)
- 1.3: Definitions and Notation
- 1.4: Diameter
- 1.5: Diameter and Trees
- 1.6: Diameters of Random Graphs (Optional/Advanced 11:12)
- 1.7: Diameters in the World
- 1.8: Degree Distributions
- 1.9: Clustering
- 1.10: Week 1 Wrap
- 2.1: Homophily
- 2.2: Dynamics and Tie Strength
- 2.3: Centrality Measures
- 2.4: Centrality – Eigenvector Measures
- 2.5a: Application - Centrality Measures
- 2.5b: Application – Diffusion Centrality
- 2.6: Random Networks
- 2.7: Random Networks - Thresholds and Phase Transitions
- 2.8: A Threshold Theorem (optional/advanced 13:00)
- 2.9: A Small World Model
- 2.10 Week 2 Wrap
- 3.1: Growing Random Networks
- 3.2: Mean Field Approximations
- 3.3: Preferential Attachment
- 3.4: Hybrid Models
- 3.5: Fitting Hybrid Models
- 3.6: Block Models
- 3.7: ERGMs
- 3.8: Estimating ERGMs
- 3.9: SERGMs
- 3.10: SUGMs
- 3.11: Estimating SUGMs (Optional/Advanced 21:03)
- 3.12: Week 3 Wrap
- 4.1: Strategic Network Formation
- 4.2: Pairwise Stability and Efficiency
- 4.3: Connections Model
- 4.4: Efficiency in the Connections Model (Optional/Advanced 12:41)
- 4.5: Pairwise Stability in the Connections Model
- 4.6: Externalities and the Coauthor Model
- 4.7: Network Formation and Transfers
- 4.8: Heterogeneity in Strategic Models
- 4.9: SUGMs and Strategic Network Formation (Optional/Advanced 13:47)
- 4.10: Pairwise Nash Stability (Optional/Advanced 11:34)
- 4.11: Dynamic Strategic Network Formation (Optional/Advanced 11:57)
- 4.12: Evolution and Stochastics (Optinoal/Advanced 16:05)
- 4.13: Directed Network Formation (Optional/Advanced 16:38)
- 4.14: Application Structural Model (Optional/Advanced 35:06)
- 4.15: Week 4 Wrap
- 5.1: Diffusion
- 5.2: Bass Model
- 5.3: Diffusion on Random Networks
- 5.4: Giant Component Poisson Case
- 5.5: SIS Model
- 5.6: Solving the SIS Model
- 5.7: Solving the SIS Model - Ordering (Optional/Advanced 24:16)
- 5.8a: Fitting a Diffusion Model to Data (Optional/Advanced 22:47)
- 5.8b: Application: Financial Contagions (Optional/Advanced 12:47)
- 5.8c: Application: Financial Contagions - Simulations (Optional/Advanced 13:41)
- 5.9: Diffusion Summary
- 5.10: Week 5 Wrap
- 6.1: Learning
- 6.2: DeGroot Model
- 6.3: Convergence in DeGroot Model
- 6.4: Proof of Convergence Theorem (Optional/Advanced 10:25)
- 6.5: Influence
- 6.6: Examples of Influence
- 6.7: Information Aggregation
- 6.8: Learning Summary
- 6.9: Week 6 Wrap
- 7.1: Games on Networks
- 7.2: Complements and Substitutes
- 7.3: Properties of Equilibria
- 7.4: Multiple Equilibria
- 7.5: An Application
- 7.6: Beyond 0-1 Choices
- 7.7: A Linear Quadratic Model
- 7.8: RepeatedGames and Networks
- 7.9: Week 7 Wrap
- 7.9b: Course Wrap