Changes in Attitude: Predicting Large-Scale Social Shifts
Why This Project Is Important
The ability to more accurately predict large-scale social change is crucial to the long-term success of policy. Our computational simulation will be the first of its kind to employ complexity theory, social constructivism, and a nonlinear methodology to investigate norm change. This will help predict large-scale social changes—such as shifts in political attitudes or in consumer confidence.
Project Description
Social norms play a crucial role in everyday decision making, yet we are rarely cognizant of their effects. This is what makes norms both so interesting and problematic to study; because social norms subconsciously impact our behaviors, it is difficult for researchers to first recognize—and then explain—normatively prescribed actions. Norms affect choices ranging from the benign (like what brand of toothpaste we buy) to crucial (like the inherent desire to defend members of one's own social group). We aim to explain how and why norms change over time by fusing the dynamic theory of social constructivism with a complex, agent-based computer simulation. Current models are highly static, resulting in a breakdown whenever norm adherence changes over time. We plan to develop a new computational simulation, which will provide the social sciences community with new tools capable of investigating complex and dynamic social phenomena. With additional funding, we will be able to develop a new computer program modeling these phenomena and present our work at conferences to foster collaborative channels for future research.
Meet the Researcher
Mark Rouleau
I have extensive interdisciplinary experience using Agent-Based Modeling (ABM) and other computer programming techniques to investigate a wide variety of social science phenomenon. At the University of Delaware, in collaboration with my thesis advisor, I developed an agent-based simulation to investigate norm competition in international climate-change policy. In collaboration with political scientists from George Mason University and Harvard University, I was the lead programmer for the development of an automated voter-redistricting program, using the optimization technique of simulated annealing to generate alternative policy scenarios for the Joyce Foundation. In collaboration with George Mason University's Center for Social Complexity, Yale University's Department of Archaeology, and the US Department of State, I was the lead programmer for multiple ABM simulations investigating the socio-environmental dynamics of civil unrest. Finally, I conducted simulation research as an assistant economist with the US Department of Agriculture, developing an ABM simulation to assess the viability of Water Quality Trading markets. The framework of this Water Quality Trading model is now serving as the foundation to my current research with Dr. Mayer investigating the land-use decision-making processes of private forest owners in the Upper Peninsula of Michigan.
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What Your Donation Can Help Us Do:
- Build a new decision-making simulation to address norm changes
- Present our new computer model at social science conferences
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