关于此课程： 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
此课程适用人群： This course is aimed at people who are interested in understanding how computational models can be used to answer complex social questions. While experience with mathematical reasoning is helpful, there are no pre-requisites for this course. The material in each module is appropriate for students of any skill level. For college and graduate students who wish to engage with the material in greater depth, each module comes with a NetLogo model that you can download, explore, and build on.
教学方： Damon Centola, Associate Professor
Annenberg School for Communication
| 级别 | Beginner |
| 承诺学习时间 | 2-3 hours/ week |
| 语言 | English |
| 如何通过 | 通过所有计分作业以完成课程。 |
| 用户评分 |
- 视频: 1.0 Course Introduction and Objectives
- 视频: 1.1 The Substantive Problem: Micromotives and Macrobehavior
- 视频: 1.2 What are Agent-Based Models?
- 视频: 1.3 Formal Model of Segregation
- 视频: 1.4 Exploring Schelling's Segregation Model
- 视频: 1.5 How to Download and Use NetLogo
- 视频: 1.6 Using NetLogo: Schelling's Segregation Model
- 视频: 2.1 Network Science: Mapping a Connected World
- 视频: 2.2 Introduction to Network Science
- 视频: 2.3 Types of Networks: Lattice Graph
- 视频: 2.4 Types of Networks: Random Graph
- 视频: 2.5 Using NetLogo: Properties of the Small World Network
- 视频: 2.6 Using NetLogo: Information Diffusion in Small World Networks
- 视频: 2.7 Conclusions: Life in a Small World
- 视频: 3.1 Social Contagions: Beyond Information Diffusion
- 视频: 3.2 From Simple to Complex Contagions
- 视频: 3.3 How to Model Complex Contagions
- 视频: 3.4 Threshold Models in Networks
- 视频: 3.5 Using NetLogo: Complex Contagions in Small World Networks
- 视频: 3.6 Conclusion: The Spread of Behavior in a Complex World
- 视频: 4.1 The Emperor's Dilemma: Explaining Unpopular Norms
- 视频: 4.2 Components of a Norm: Compliance and Enforcement
- 视频: 4.3 Modeling Compliance and Enforcement
- 视频: 4.4 Using NetLogo: Explaining the Spread of Unpopular Norms
- 视频: 4.5 Falsification and Sufficiency in the Emperor's Dilemma
- 视频: 4.6 Self-Reinforcing Norms: A Cautionary Conclusion
- 视频: 5.1 A Startup Problem: The Emergence of Norms
- 视频: 5.2 Conventions and the Challenge of Coordination
- 视频: 5.3 Modelling Pairwise Coordination in Networks
- 视频: 5.4 Using NetLogo: Coordination in Networks
- 视频: 5.5 How do norms emerge? Global Agreement from Peer-to-Peer Interation
- 视频: 6.1 Exploration and Exploitation: Networks of Innovation
- 视频: 6.2 Modeling Complex Problems
- 视频: 6.3 Modeling Problem-Solving in Teams
- 视频: 6.4 Thinking about Models: Problem-Solving in the Real World
- 视频: 6.5 Using NetLogo: Complex Problem Solving in Networks
- 视频: 6.6 Conclusions: The Two Pizza Rule
- 视频: 6.7 Course Conclusions: The Network Dynamics of Social Behavior
Cada curso é como um livro didático interativo, com vídeos pré-gravados, testes e projetos.
Conecte-se com milhares de outros aprendizes, debata ideias, discuta sobre os materiais do curso e obtenha ajuda para dominar conceitos.
Obtenha reconhecimento oficial pelo seu trabalho e compartilhe seu sucesso com amigos, colegas e empregadores.
The course gives a very good overview of the main insights and is enjoyable at the same time. Great course that would deserve a five-star rating if it would not be for the many typos, incomplete sentences in the tests, and errors in the videos.
i started this course after i read a book 'Linked' and became interested in network science. Although English is foreign language to me and Netlogo is new to me, i didn't have any difficulties understanding the course because it contains lots of examples and easy explanations. and i'm satisfied as i learned how social network works in our society. Thanks!
Content is neatly laid out, not mathematically rigorous as I believe course is targeting a wider set of audience. Week 2 material can be improved with regard to clarity about the different types of networks.
very good overview. i'm missing the maths behind the theory which will enable me to apply the knowledge to own problems