Network Dynamics of Social Behavior
Explore how social networks influence behavior, norms, and innovation. Learn agent-based modeling to understand complex social phenomena.
Explore how social networks influence behavior, norms, and innovation. Learn agent-based modeling to understand complex social phenomena.
This course examines the network dynamics that shape social behavior, covering topics such as the spread of ideas, emergence of social norms, and team problem-solving. Students learn to use agent-based models and network theory to analyze complex social phenomena. The curriculum includes six modules, each focusing on a specific research puzzle, from Schelling's segregation model to the dynamics of problem-solving in networks. Through interactive computational models using NetLogo, participants gain hands-on experience in modeling social processes. The course emphasizes how minor changes in network structure can lead to significant shifts in collective behavior, providing insights into social movements, cultural changes, and organizational dynamics.
4.6
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What you'll learn
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 growth in social movements and changes in cultural norms
Use NetLogo to create and analyze agent-based models of social phenomena
Skills you'll gain
This course includes:
2.22 Hours PreRecorded video
6 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
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There are 6 modules in this course
This course provides an in-depth exploration of the network dynamics that shape social behavior. It covers six key areas: Schelling's segregation model, diffusion in small worlds, complex contagions, the spread of unpopular norms, emergence of conventions, and problem-solving in networks. The curriculum combines theoretical concepts with practical applications using NetLogo software for agent-based modeling. Students learn how to analyze and model complex social phenomena, from the spread of ideas and behaviors to the emergence of social norms and conventions. The course emphasizes the often counterintuitive ways in which individual actions can lead to collective outcomes, and how network structures influence social change, innovation, and problem-solving in teams.
Course Introduction and Schelling's Segregation Model
Module 1 · 0 Hours to complete
Diffusion in Small Worlds
Module 2 · 0 Hours to complete
Complex Contagions and the Weakness of Long Ties
Module 3 · 0 Hours to complete
Emperor's Dilemma and the Spread of Unpopular Norms
Module 4 · 0 Hours to complete
The Spontaneous Emergence of Conventions
Module 5 · 0 Hours to complete
Problem Solving in Networks
Module 6 · 1 Hours to complete
Fee Structure
Payment options
Financial Aid
Instructor
Damon Centola, Professor of Communication, Sociology, and Engineering at the University of Pennsylvania
Damon Centola is a Professor of Communication, Sociology, and Engineering at the University of Pennsylvania, recognized for his research on how behavior spreads through social networks. He is the author of influential works including Change: How to Make Big Things Happen and How Behavior Spreads: The Science of Complex Contagions. Before joining Penn, he served as an Assistant Professor at MIT and was a Robert Wood Johnson Fellow at Harvard University. Centola completed his Ph.D. in sociology at Cornell University and is currently a Fellow at the Center for Advanced Study in the Behavioral Sciences at Stanford University. His course Network Dynamics of Social Behavior explores the mechanisms behind social influence and behavior change. Through his research, Centola has contributed significantly to understanding complex contagions and the dynamics of social behavior across various contexts, including health and technology.
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4.6 course rating
386 ratings
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