Agent-based models in sociology

This article looks at 20 years of applications of agent-based models (ABMs) in sociology and, in particular, their explanatory achievements and methodological insights. These applications have helped sociologists to examine agent interaction in social outcomes and have helped shift analyses away from structural and aggregate factors, to the role of agency. They have improved the realism of the micro-behavioral foundations of sociological models, by complementing analytic modeling and game theory-inspired analyses. Secondly, they have helped us to dissect the role of social structures in constraining individual behavior more precisely than in variable-based sociology. Finally, simulation outcomes have given us a more dynamic view of the interplay between individual behavior and social structures, thus promoting a more evolutionary and process-based approach to social facts. Attention here has been paid to social norms, social influence, and culture dynamics, across different disciplines such as behavioral sciences, complexity science, sociology, and economics. We argue that these applications can help sociology to achieve more rigorous research standards, by promoting a modeling environment and providing tighter cross-disciplinary integration. Recently, certain methodological improvements toward model standardization, replication, and validation have been achieved. As a result, the impact of these models in sociology is expected to grow even more in the future.