Network Dynamics of Social Behavior

Go to Course: https://www.coursera.org/learn/networkdynamics

Introduction

### Course Review: Network Dynamics of Social Behavior on Coursera If you've ever pondered the intricate ways in which social movements and behaviors evolve, or why certain ideas spread through culture while others seem to languish in obscurity, the course "Network Dynamics of Social Behavior" on Coursera is a must-take. This engaging course delves into the complex world of social dynamics through the lens of agent-based modeling and social network theory, arming you with the tools to analyze the forces shaping our collective behaviors. #### Course Overview The course starts with a captivating premise: How do revolutions occur seemingly out of nowhere? Why do social norms shift so rapidly? Each week tackles fundamental questions that resonate deeply in society today, from the rapid acceptance of same-sex marriage to the emergence of social innovations. You’ll gain insights into social evolution, exploring not just theoretical concepts but also practical applications. #### Syllabus Breakdown 1. **Course Introduction and Schelling's Segregation Model**: The course kicks off with a foundational introduction to agent-based modeling. You'll explore Thomas Schelling's Segregation Model, illustrating how individual preferences can lead to collective segregation. Engaging with tools like NetLogo, students will learn how to visualize complex social phenomena. 2. **Diffusion in Small Worlds**: In this module, you’ll investigate the "small worlds" paradox and how information spreads through networks. By studying contagion models, you’ll grasp the interplay between network structure and the velocity of information dissemination. 3. **Complex Contagions and the Weakness of Long Ties**: Building on the previous week, students will confront the limitations of traditional contagion models. This segment explores the concept of complex contagions, emphasizing the need for social reinforcement and the surprising results when networks grow smaller. 4. **Emperor's Dilemma and the Spread of Unpopular Norms**: Inspired by Andersen’s tale, this week demonstrates the fascinating dynamics behind the spread of behaviors that may not enjoy widespread personal approval. You’ll learn about the interaction between public and private beliefs as drivers of social phenomena. 5. **The Spontaneous Emergence of Conventions**: Here, the course probes how societal norms emerge organically, without central coordination. Through an agent-based model, students will gain a clearer understanding of how local interactions can lead to widespread convention adoption. 6. **Problem Solving in Networks**: The concluding module tackles the organization of teams for optimal innovation. Students will learn about the delicate balance between communication and clustering in problem-solving settings, reinforcing the fundamental concepts through agent-based modeling. #### Why You Should Take This Course - **Interdisciplinary Approach**: This course bridges sociology, psychology, and computer science, providing a holistic understanding of social behavior dynamics. - **Practical Tools**: The use of NetLogo not only enhances theoretical understanding but also empowers learners with the skills to model real-world scenarios, crucial for those interested in research or careers in social sciences, policy-making, or organizational behavior. - **Engaging Content**: Each lesson is thoughtfully constructed to stimulate both intellectual curiosity and practical application, making complex theories accessible to a broad audience. - **Real-World Applications**: Understanding social dynamics has never been more critical, especially in our rapidly changing society. The insights could be invaluable whether you are a student, a professional in social policy, or simply someone keen to understand the underlying patterns of human behavior. #### Conclusion Overall, "Network Dynamics of Social Behavior" on Coursera is an enlightening and challenging course. It caters not only to those with academic interests in social behavior but also to professionals seeking deeper insights into societal changes. If you’re ready to unravel the complexities of social dynamics and harness the power of network theory, I highly recommend enrolling in this course today. It promises to reshape your understanding of how social behaviors evolve and can arm you with the analytical tools to examine and influence such dynamics in the future.

Syllabus

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.

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.

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.

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.

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.

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.