In order to understand the relationship between people, physical space, and future change, a diverse set of methods is used that focuses around three main research areas: agent-based modeling (ABM), geographical information science (GIS) and social network analysis (SNA). The intersection between these research areas can be represented through computational social science (CSS), which lies at the foundation of this research as it represents the interdisciplinary science that uses computational modeling and related techniques to study complex social systems.

A computational model of the riots that broke-out in an urban slum after the 2007 Kenyan presidential election is used to demonstrate the value of integrating these research areas. Characteristics such as poverty, overpopulation, and a growing youth bulge put urban slums at greater risk for violence. Using empirical data for which to build the landscape and provide agents with unique attributes, an ABM is integrated with SNA and GIS to simulate the outbreak of riots. The model investigates the role individual identity, group identity, and social influence played on the occurrence and intensity of riots. Model results find that the cyclical nature in the emergence and dissolution of rioting is due to positive reinforcement, an effect that can be largely attributed to the agents’ social networks, and thus their interactions and influences through these networks. Riots arise from the interactions between individuals with unique attributes, all within a connected social network over a physical environment. In order to gain a better understanding of the macro-level patterns that emerge, the nonlinear and reinforcing nature of this system is modeled from the bottom-up.

Published by Pires, October 07, 2014