Network Dynamics of Social Behavior

宾夕法尼亚大学

课程信息

15,985 次近期查看

How do revolutions emerge without anyone expecting them?  How did social norms about same sex marriage change more rapidly than anyone anticipated?  Why do some social innovations take off with relative ease, while others struggle for years without spreading?  More generally, what are the forces that control the process of social evolution –from the fashions that we wear, to our beliefs about religious tolerance, to our ideas about the process of scientific discovery and the best ways to manage complex research organizations? 
The social world is complex and full of surprises. Our experiences and intuitions about the social world as individuals are often quite different from the behaviors that we observe emerging in large societies. Even minor changes to the structure of a social network - changes that are unobservable to individuals within those networks - can lead to radical shifts in the spread of new ideas and behaviors through a population. These “invisible” mathematical properties of social networks have powerful implications for the ways that teams solve problems, the social norms that are likely to emerge, and even the very future of our society.  

This course condenses the last decade of cutting-edge research on these topics into six modules.  Each module provides an in-depth look at a particular research puzzle -with a focus on agent-based models and network theories of social change -and provides an interactive computational model for you try out and to use for making your own explorations!  


Learning objectives - after this course, students will be able to...
- explain how computer models are used to study challenging social problems 
- describe how networks are used to represent the structure of social relationships 
- show how individual actions can lead to unintended collective behaviors
- provide concrete examples of how social networks can influence social change 
- discuss how diffusion processes can explain the growth social movements, changes in cultural norms, and the success of team problem solving

学生职业成果

20%

完成这些课程后已开始新的职业生涯

11%

通过此课程获得实实在在的工作福利

17%

加薪或升职

可分享的证书

完成后获得证书

100% 在线

立即开始，按照自己的计划学习。

可灵活调整截止日期

根据您的日程表重置截止日期。

初级

完成时间大约为4 小时

英语（English）

字幕：英语（English）, 中文（简体）

学生职业成果

20%

完成这些课程后已开始新的职业生涯

11%

通过此课程获得实实在在的工作福利

17%

加薪或升职

可分享的证书

完成后获得证书

100% 在线

立即开始，按照自己的计划学习。

可灵活调整截止日期

根据您的日程表重置截止日期。

初级

完成时间大约为4 小时

英语（English）

字幕：英语（English）, 中文（简体）

讲师

授课教师评分

4.61/5 （28 个评分）

Damon Centola

Associate Professor

Annenberg School for Communication

7,772 个学生

1 门课程

提供方

宾夕法尼亚大学

The University of Pennsylvania (commonly referred to as Penn) is a private university, located in Philadelphia, Pennsylvania, United States. A member of the Ivy League, Penn is the fourth-oldest institution of higher education in the United States, and considers itself to be the first university in the United States with both undergraduate and graduate studies.

教学大纲 - 您将从这门课程中学到什么

周

周 1

完成时间为 1 小时

Course Introduction and Schelling's Segregation Model

This week will introduce students to agent-based modeling and social network theory. We will present one of the earliest and most famous agent-based models, Thomas Schelling’s model of segregation, which shows how segregation can emerge in a population even when people individually prefer diversity. This week will demonstrate this model both conceptually and with NetLogo, and illustrate how agent-based models can be used to demonstrate sufficient conditions for the emergence of social phenomena.

完成时间为 1 小时

7 个视频（总计 20 分钟）

7 个视频

1.0 Course Introduction and Objectives6分钟

1.1 The Substantive Problem: Micromotives and Macrobehavior1分钟

1.2 What are Agent-Based Models?2分钟

1.3 Formal Model of Segregation1分钟

1.4 Exploring Schelling's Segregation Model1分钟

1.5 How to Download and Use NetLogo2分钟

1.6 Using NetLogo: Schelling's Segregation Model4分钟

1 个练习

Week 116分钟

周

周 2

完成时间为 1 小时

Diffusion in Small Worlds

This week will introduce students to social network theory and the “small worlds” paradox. We will introduce contagion models of diffusion, and discuss how network structure can impact the speed with which information spreads through a population. This week includes both high level conceptual overviews of social network theory, explaining how networks are used to represent complex social relationships, as well as technical descriptions of two basic types of networks.

完成时间为 1 小时

7 个视频（总计 25 分钟）

7 个视频

2.1 Network Science: Mapping a Connected World1分钟

2.2 Introduction to Network Science5分钟

2.3 Types of Networks: Lattice Graph5分钟

2.4 Types of Networks: Random Graph4分钟

2.5 Using NetLogo: Properties of the Small World Network2分钟

2.6 Using NetLogo: Information Diffusion in Small World Networks3分钟

2.7 Conclusions: Life in a Small World2分钟

1 个练习

Week 218分钟

周

周 3

完成时间为 1 小时

Complex Contagions and the Weakness of Long Ties

This week will begin by discussing the limitations of simple disease-like models of social contagion, introducing the idea of “complex contagions” to model people’s frequent need for social reinforcement before spreading a piece of information or behavior. While simple contagions always spread faster as networks get smaller, this week will demonstrate the paradoxical nature of complex contagions, which can spread slower (or not at all!) in the smallest networks.

完成时间为 1 小时

6 个视频（总计 26 分钟）

6 个视频

3.1 Social Contagions: Beyond Information Diffusion1分钟

3.2 From Simple to Complex Contagions4分钟

3.3 How to Model Complex Contagions4分钟

3.4 Threshold Models in Networks9分钟

3.5 Using NetLogo: Complex Contagions in Small World Networks2分钟

3.6 Conclusion: The Spread of Behavior in a Complex World3分钟

1 个练习

Week 324分钟

周

周 4

完成时间为 1 小时

Emperor's Dilemma and the Spread of Unpopular Norms

How can behaviors become popular even when most people dislike them? This week will introduce a model based on the classic allegory by Hans Christian Anderson, “The Emperor’s New Clothes.” We will first provide a conceptual overview of the model, discussing the role of private versus public beliefs and the enforcement of social norms. We will then present this model in NetLogo, showing which conditions favor the spread of unpopular behaviors.

完成时间为 1 小时

6 个视频（总计 17 分钟）

6 个视频

4.1 The Emperor's Dilemma: Explaining Unpopular Norms2分钟

4.2 Components of a Norm: Compliance and Enforcement1分钟

4.3 Modeling Compliance and Enforcement2分钟

4.4 Using NetLogo: Explaining the Spread of Unpopular Norms7分钟

4.5 Falsification and Sufficiency in the Emperor's Dilemma1分钟

4.6 Self-Reinforcing Norms: A Cautionary Conclusion1分钟

1 个练习

Week 416分钟

周

周 5

完成时间为 1 小时

The Spontaneous Emergence of Conventions

This week will tackle another puzzle in social conventions: how can populations reach widely shared social conventions in the absence of any central organizing mechanism? We will begin by discussing classic explanations for the emergence of conventions, and why these explanations are insufficient to explain our social world. We will then discuss an agent-based model of conventions that builds on a model of local peer-to-peer coordination, and use NetLogo to show how local interactions can generate global convergence.

完成时间为 1 小时

5 个视频（总计 16 分钟）, 1 个阅读材料, 1 个测验

5 个视频

5.1 A Startup Problem: The Emergence of Norms5分钟

5.2 Conventions and the Challenge of Coordination2分钟

5.3 Modelling Pairwise Coordination in Networks3分钟

5.4 Using NetLogo: Coordination in Networks2分钟

5.5 How do norms emerge? Global Agreement from Peer-to-Peer Interation2分钟

1 个阅读材料

Optional Reading: Creating Critical Mass10分钟

1 个练习

Week 520分钟

周

周 6

完成时间为 1 小时

Problem Solving in Networks

How can you best organize a team to produce innovative solutions to complex problems? If people on the team can’t communicate, then they can’t share strategies, and won’t learn from each other’s success. But if they communicate too much, they’ll cluster around just a few ideas, and won’t explore the entire problem space. This week introduces an agent-based model of problem solving and shows how network structure can be used to navigate this classic exploration/exploitation trade-off.

完成时间为 1 小时

7 个视频（总计 31 分钟）

7 个视频

6.1 Exploration and Exploitation: Networks of Innovation2分钟

6.2 Modeling Complex Problems7分钟

6.3 Modeling Problem-Solving in Teams2分钟

6.4 Thinking about Models: Problem-Solving in the Real World1分钟

6.5 Using NetLogo: Complex Problem Solving in Networks9分钟

6.6 Conclusions: The Two Pizza Rule1分钟

6.7 Course Conclusions: The Network Dynamics of Social Behavior4分钟

1 个练习

Week 618分钟

常见问题

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Network Dynamics of Social Behavior