Welcome to the Contagion Models module! This module explores how ideas, behaviors, diseases, and innovations spread through social networks and populations. Building on threshold models from our segregation module, we’ll examine both biological and social contagion processes using computational modeling approaches.
Contagion models help us understand how things spread - from infectious diseases to social movements, from rumors to technological innovations. Through agent-based modeling, we’ll explore different mechanisms of transmission, the role of network structure, and intervention strategies for controlling or promoting different types of contagion. We’ll see how Granovetter’s threshold models Granovetter (1978) provide a foundation for understanding collective behavior and social mobilization.
Module Duration: 2 weeks
👩🏾🎓 Student Learning Objectives (SLOs)¶
By the end of this module, students will be able to:
Core SLOs¶
Construct data-driven, mathematical, statistical, and/or software models, analyzing their results to answer questions, solve problems, support arguments, draw conclusions, make predictions, and/or identify possible causal relationships.
Identify and use tools appropriate for solving a given problem, such as algebra, calculus, and other mathematical tools; spreadsheets, databases, and data-analysis software; domain-specific software; and/or writing one’s own software.
Conceptual SLOs¶
Distinguish between different types of contagion (biological, social, behavioral)
Explain the role of network structure in contagion processes
Analyze the dynamics of epidemic curves and tipping points
Understand concepts like basic reproduction number (R₀) and herd immunity
Connect threshold models to collective behavior and social movements
Evaluate how individual thresholds aggregate to produce collective outcomes
Technical SLOs¶
Implement SIR and SEIR epidemiological models in NetLogo
Model contagion on different network topologies
Create threshold-based models for collective behavior
Analyze the effects of intervention strategies on spread dynamics
Visualize and interpret contagion simulation results
Critical Thinking¶
Evaluate the effectiveness of public health interventions
Assess the parallels and differences between biological and social contagion
Critique assumptions in contagion models and their real-world applicability
Analyze the ethical implications of contagion research and policy
Compare model predictions with real-world contagion phenomena
Communication¶
Present findings from contagion simulation experiments clearly
Discuss the policy implications of different intervention strategies
Explain complex contagion concepts to non-technical audiences
Connect model insights to contemporary public health and social issues
📚 Readings and Extra Materials¶
🔒 Required Readings¶
The required and optional readings for this module are available by 📖 clicking in this link. You have to be logged in with your Calvin account to access them.
📖 Mark Granovetter (1978) “Threshold Models of Collective Behavior”.
📖 Damon Centola (2010) “The Spread of Behavior in an Online Social Network Experiment”. Science, 329(5996), 1194–1197.
📖 Damon Centola & Michael Macy (2007) “Complex Contagions and the Weakness of Long Ties”. American Journal of Sociology, 113(3), 702–734.
🔓 Recommended Readings¶
📖 Centola (2018). “How Behavior Spreads”. Chapter 3: Social Contagion.
📖 Watts, D. J. (2002). “A simple model of global cascades on random networks”. Proceedings of the National Academy of Sciences, 99(9), 5766–5771.
📖 González-Bailón, S. (2011). “The dynamics of protest recruitment through online social networks”. Scientific Reports, 1(1), 197.
📖 Steinert-Threlkeld, Z. C. (2017). “Spontaneous collective action: Peripheral mobilization during the Arab Spring”. American Political Science Review, 111(2), 379-403.
📖 Smaldino (2023). Modeling social behavior: Mathematical and agent-based models of social dynamics and cultural evolution. Chapters 4 and 5.
📽️ Inspirational Videos¶
How Behavior Spreads: The Science of Complex Contagions (Damon Centola)
The Hidden Influence of Social Networks (Nicholas Christakis)
Feeling Their Vibes? Uncovering the Mystery of Emotional Contagion 🧠💫
🔗 Online Resources¶
- Granovetter, M. (1978). Threshold models of collective behavior. American Journal of Sociology, 83(6), 1420–1443.
- Granovetter, M. (1978). Threshold Models of Collective Behavior. American Journal of Sociology, 83(6), 1420–1443. 10.1086/226707
- Centola, D. (2010). The Spread of Behavior in an Online Social Network Experiment. Science, 329(5996), 1194–1197. 10.1126/science.1185231
- Centola, D., & Macy, M. (2007). Complex Contagions and the Weakness of Long Ties. American Journal of Sociology, 113(3), 702–734. 10.1086/521848
- Centola, D. (2018). How behavior spreads: The science of complex contagions (Vol. 3). Princeton University Press Princeton, NJ.
- Watts, D. J. (2002). A simple model of global cascades on random networks. Proceedings of the National Academy of Sciences, 99(9), 5766–5771. 10.1073/pnas.082090499
- González-Bailón, S., Borge-Holthoefer, J., Rivero, A., & Moreno, Y. (2011). The Dynamics of Protest Recruitment through an Online Network. Scientific Reports, 1(1). 10.1038/srep00197
- STEINERT-THRELKELD, Z. C. (2017). Spontaneous Collective Action: Peripheral Mobilization During the Arab Spring. American Political Science Review, 111(2), 379–403. 10.1017/s0003055416000769
- Smaldino, P. (2023). Modeling Social Behavior: Mathematical and Agent-based Models of Social Dynamics and Cultural Evolution.