Social and Economic Networks: Models and Analysis

开始时间: 04/22/2022 持续时间: 9 weeks

所在平台: CourseraArchive

课程类别: 计算机科学

大学或机构: Stanford University（斯坦福大学）

授课老师： Matthew O. Jackson

课程主页: https://www.coursera.org/course/networksonline

课程评论: 3 个评论

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课程详情

Social networks pervade our social and economic lives. They play a central role in the transmission of information about job opportunities and are critical to the trade of many goods and services. They are important in determining which products we buy, which languages we speak, how we vote, as well as whether or not we decide to become criminals, how much education we obtain, and our likelihood of succeeding professionally. The countless ways in which network structures affect our well-being make it critical to understand how social network structures impact behavior, which network structures are likely to emerge in a society, and why we organize ourselves as we do. This course provides an overview and synthesis of research on social and economic networks, drawing on studies by sociologists, economists, computer scientists, physicists, and mathematicians.

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.

课程大纲

Week 1: 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

Week 2: 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,

Week 3: Random Networks

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

Week 4: 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

Week 5: Diffusion on Networks.

Empirical Background, The Bass Model, Random Network Models of Contagion, The SIS model, Fitting a Simulated Model to Data

Week 6: Learning on Networks.

Bayesian Learning on Networks, The DeGroot Model of Learning on a Network, Convergence of Beliefs, The Wisdom of Crowds, How Influence depends on Network Position.

Week 7: Games on Networks.

Network Games, Peer Influences: Strategic Complements and Substitutes, the Relation between Network Structure and Behavior, A Linear Quadratic Game, Repeated Interactions and Network Structures.

课程评论(3条)

0	都柏林的老菲利普 2014-02-01 12:27 0 票支持; 0 票反对讲了不少social sciences方面network analysis的方法，还是挺有启发性的。如果想学计算机方面的图论方面的应用，可以看看Luca Trevesan的那门expander graph

0	MarTierra 2013-08-13 03:57 0 票支持; 0 票反对作业难度略低。对实际操作可能没什么帮助，收获在于建立了network thinking。教这课的教授是个大牛，他还开了game theory的课。不知道Michigan那个network analysis怎么样。

0	呵公要当攻城狮 2013-05-14 16:45 0 票支持; 0 票反对课程内容还算有趣，但是比较针对研究，实用性不强，会介绍一些Social Network的基本概念，比较偏向经济理论，作业也比较水。我还在学部分原因是已经付出了5个礼拜的沉默成本。。。

课程简介

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.