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.
Redes Sociais e Econômicas: Modelos e Análises
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Redes Sociais e Econômicas: Modelos e Análises
Universidade de Stanford
Informações sobre o curso
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Habilidades que você terá
Social NetworkGame TheoryNetwork AnalysisNetwork Theory
Resultados de carreira do aprendiz
25%
comecei uma nova carreira após concluir estes cursos
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Comece imediatamente e aprenda em seu próprio cronograma.
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Nível avançado
Aprox. 25 horas para completar
Inglês
Legendas: Inglês
Programa - O que você aprenderá com este curso
3 horas para concluir
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
3 horas para concluir
12 vídeos (Total 118 mín.), 3 leituras, 3 testes
12 videos
1.1: Introduction9min
1.2: Examples and Challenges 15min
1.2.5 Background Definitions and Notation (Basic - Skip if familiar 8:23)8min
1.3: Definitions and Notation 14min
1.4: Diameter 16min
1.5: Diameter and Trees 6min
1.6: Diameters of Random Graphs (Optional/Advanced 11:12)11min
1.7: Diameters in the World 6min
1.8: Degree Distributions 13min
1.9: Clustering 8min
1.10: Week 1 Wrap2min
3 leituras
Syllabus10min
Slides from Lecture 1, with References10min
OPTIONAL - Advanced Problem Set 110min
3 exercícios práticos
Quiz Week 128min
Problem Set 112min
Optional: Empirical Analysis of Network Data using Gephi or Pajek8min
3 horas para concluir
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
3 horas para concluir
11 vídeos (Total 105 mín.), 3 leituras, 3 testes
11 videos
2.1: Homophily10min
2.2: Dynamics and Tie Strength 6min
2.3: Centrality Measures 14min
2.4: Centrality – Eigenvector Measures 13min
2.5a: Application - Centrality Measures 12min
2.5b: Application – Diffusion Centrality 6min
2.6: Random Networks 10min
2.7: Random Networks - Thresholds and Phase Transitions 7min
2.8: A Threshold Theorem (optional/advanced 13:00)13min
2.9: A Small World Model 7min
2.10 Week 2 Wrap3min
3 leituras
Slides from Lecture 2, with references10min
OPTIONAL - Advanced Problem Set 210min
OPTIONAL - Solutions to Advanced PS 110min
3 exercícios práticos
Quiz Week 216min
Problem Set 210min
Optional: Empirical Analysis of Network Data6min
4 horas para concluir
Random Networks
Poisson Random Networks, Exponential Random Graph Models, Growing Random Networks, Preferential Attachment and Power Laws, Hybrid models of Network Formation.
4 horas para concluir
12 vídeos (Total 143 mín.), 3 leituras, 4 testes
12 videos
3.2: Mean Field Approximations 8min
3.3: Preferential Attachment 10min
3.4: Hybrid Models 14min
3.5: Fitting Hybrid Models 17min
3.6: Block Models 9min
3.7: ERGMs 9min
3.8: Estimating ERGMs 15min
3.9: SERGMs 9min
3.10: SUGMs 6min
3.11: Estimating SUGMs (Optional/Advanced 21:03)21min
3.12: Week 3 Wrap3min
3 leituras
Slides from Lecture 3, with references10min
OPTIONAL - Advanced Problem Set 310min
OPTIONAL - Solutions to Advanced PS 210min
4 exercícios práticos
Quiz Week 326min
Problem Set 36min
Optional: Empirical Analysis of Network Data4min
Optional: Using Statnet in R to Estimate an ERGM6min
5 horas para concluir
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.
5 horas para concluir
15 vídeos (Total 209 mín.), 3 leituras, 2 testes
15 videos
4.2: Pairwise Stability and Efficiency 15min
4.3: Connections Model 11min
4.4: Efficiency in the Connections Model (Optional/Advanced 12:41)12min
4.5: Pairwise Stability in the Connections Model 6min
4.6: Externalities and the Coauthor Model 11min
4.7: Network Formation and Transfers 16min
4.8: Heterogeneity in Strategic Models 13min
4.9: SUGMs and Strategic Network Formation (Optional/Advanced 13:47)13min
4.10: Pairwise Nash Stability (Optional/Advanced 11:34)11min
4.11: Dynamic Strategic Network Formation (Optional/Advanced 11:57)11min
4.12: Evolution and Stochastics (Optinoal/Advanced 16:05)16min
4.13: Directed Network Formation (Optional/Advanced 16:38)16min
4.14: Application Structural Model (Optional/Advanced 35:06)35min
4.15: Week 4 Wrap4min
3 leituras
Slides from Lecture 4, with references10min
OPTIONAL - Advanced Problem Set 410min
OPTIONAL - Solutions to Advanced PS 310min
2 exercícios práticos
Quiz Week 436min
Problem Set 414min
Avaliações
Principais avaliações do REDES SOCIAIS E ECONÔMICAS: MODELOS E ANÁLISES
por MRNov 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 :)
por SWAug 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.
por MGApr 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.
por TCApr 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.
por HTDec 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.
por ACSep 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.
por OJJul 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.
por GPJun 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
Sobre Universidade de Stanford
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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