Agent-Based Modeling as a Tool for Studying Social Identity Processes: The Case of Optimal Distinctiveness Theory: Cynthia L. Pickett, Paul E. Smaldino, and Jeffrey Schank
Researchers studying social identity and intergroup relations have traditionally approached group behavior as an interaction between the individual, the group, and the social context in which the individual and group are embedded. This approach has been quite fruitful, as evidenced by the proliferation of theories and studies over the last several decades that have identified the psychological and sociocontextual features that are likely to give rise to particular group behaviors (e.g., in-group bias, discrimination, intergroup hostility). However, these theories are based largely on how individuals are predicted to respond and behave under particular circumstances, often without explicit consideration of the interdependence among individuals or the group-level outcomes that may emerge as a result of the interactions among individual actors. This approach is similar to a traffic engineer attempting to understand traffic patterns by examining the motivations and behaviors of individual drivers. Individual-level theories may tell the engineer that drivers attempt to maximize the speed of their car and avoid erratic fellow drivers. But understanding why traffic jams occur requires consideration of how the behavior of one driver affects the behavior of multiple other drivers and how these behaviors unfold over time. In this chapter, we echo the sentiment of other researchers
(e.g., Goldstone & Janssen, 2005; Smith & Conrey, 2007) and argue that understanding group-level phenomena requires studying both individual-level processes and the global structures that emerge as a result of interactions among individuals.