Network Dynamics of Social Behavior

ペンシルベニア大学（University of Pennsylvania）

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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

受講生の就業成果

20%

コース終了後に新しいキャリアをスタートした

11%

コースが具体的なキャリアアップにつながった

17%

昇給や昇進につながった

共有できる証明書

修了時に証明書を取得

100%オンライン

自分のスケジュールですぐに学習を始めてください。

柔軟性のある期限

スケジュールに従って期限をリセットします。

初級レベル

約4時間で修了

英語

字幕：英語, 中国語（簡体）

受講生の就業成果

20%

コース終了後に新しいキャリアをスタートした

11%

コースが具体的なキャリアアップにつながった

17%

昇給や昇進につながった

共有できる証明書

修了時に証明書を取得

100%オンライン

自分のスケジュールですぐに学習を始めてください。

柔軟性のある期限

スケジュールに従って期限をリセットします。

初級レベル

約4時間で修了

英語

字幕：英語, 中国語（簡体）

講師

講師の評価

4.61/5 (28 件の評価)

Damon Centola

Associate Professor

Annenberg School for Communication

受講者7,766 名

1 コース

提供：

ペンシルベニア大学（University of Pennsylvania）

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.

シラバス - 本コースの学習内容

週

週 1

1時間で修了

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.

1時間で修了

7件のビデオ（合計20分）

7件のビデオ

1.0 Course Introduction and Objectives6 分

1.1 The Substantive Problem: Micromotives and Macrobehavior1 分

1.2 What are Agent-Based Models?2 分

1.3 Formal Model of Segregation1 分

1.4 Exploring Schelling's Segregation Model1 分

1.5 How to Download and Use NetLogo2 分

1.6 Using NetLogo: Schelling's Segregation Model4 分

1の練習問題

Week 116 分

週

週 2

1時間で修了

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.

1時間で修了

7件のビデオ（合計25分）

7件のビデオ

2.1 Network Science: Mapping a Connected World1 分

2.2 Introduction to Network Science5 分

2.3 Types of Networks: Lattice Graph5 分

2.4 Types of Networks: Random Graph4 分

2.5 Using NetLogo: Properties of the Small World Network2 分

2.6 Using NetLogo: Information Diffusion in Small World Networks3 分

2.7 Conclusions: Life in a Small World2 分

1の練習問題

Week 218 分

週

週 3

1時間で修了

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.

1時間で修了

6件のビデオ（合計26分）

6件のビデオ

3.1 Social Contagions: Beyond Information Diffusion1 分

3.2 From Simple to Complex Contagions4 分

3.3 How to Model Complex Contagions4 分

3.4 Threshold Models in Networks9 分

3.5 Using NetLogo: Complex Contagions in Small World Networks2 分

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

1の練習問題

Week 324 分

週

週 4

1時間で修了

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.

1時間で修了

6件のビデオ（合計17分）

6件のビデオ

4.1 The Emperor's Dilemma: Explaining Unpopular Norms2 分

4.2 Components of a Norm: Compliance and Enforcement1 分

4.3 Modeling Compliance and Enforcement2 分

4.4 Using NetLogo: Explaining the Spread of Unpopular Norms7 分

4.5 Falsification and Sufficiency in the Emperor's Dilemma1 分

4.6 Self-Reinforcing Norms: A Cautionary Conclusion1 分

1の練習問題

Week 416 分

週

週 5

1時間で修了

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.

1時間で修了

5件のビデオ（合計16分）, 1 reading, 1 quiz

5件のビデオ

5.1 A Startup Problem: The Emergence of Norms5 分

5.2 Conventions and the Challenge of Coordination2 分

5.3 Modelling Pairwise Coordination in Networks3 分

5.4 Using NetLogo: Coordination in Networks2 分

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

1件の学習用教材

Optional Reading: Creating Critical Mass10 分

1の練習問題

Week 520 分

週

週 6

1時間で修了

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.

1時間で修了

7件のビデオ（合計31分）

7件のビデオ

6.1 Exploration and Exploitation: Networks of Innovation2 分

6.2 Modeling Complex Problems7 分

6.3 Modeling Problem-Solving in Teams2 分

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

6.5 Using NetLogo: Complex Problem Solving in Networks9 分

6.6 Conclusions: The Two Pizza Rule1 分

6.7 Course Conclusions: The Network Dynamics of Social Behavior4 分

1の練習問題

Week 618 分

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Network Dynamics of Social Behavior