Computational Social Psychology

Computational social psychology is a branch of social psychology that uses computational methods to understand the psychological mechanisms underlying social phenomena. Computational social psychology has two pillars: computational modeling and computational analysis. Computational modeling focuses on building formal systems theories and generating hypotheses of complex social systems. Computational anlaysis foscuses on testing those hypotheses using social network analysis, psychological network analysis, spatial analysis, multi-level analysis, and various data science techniques.

Our lab develops computational models that map empirically validated psychological mechanisms of minority influence onto macro-level patterns of social change. We also use computational methods to quantify community inclusion of minority groups. To achieve these goals, we employ agent-based modeling, social simulation, social network analysis, and other tools. In addition, we develop novel research paradigms that integrate computational approaches with traditional methods in social psychology.

Agent-Based Modeling for Social Psychological Research

Agent-based modeling (ABM) offers a valuable research method for advancing psychological research on social phenomena by simulating how individual behaviors give rise to complex social patterns. Specifically, ABM offers seven benefits:

Formal theories of complex social systems
Multilevel causation & emergence
Temporal & nonlinear dynamics
Completeness of theories
Persons-environment interaction
Bridging psychology and policy
Uncovering unknown unknowns & prediction limits

We introduce a new research approach—the minimal society paradigm—and a modeling strategy called principle-oriented modeling. This framework integrates ABM into psychological research by supporting theory building through minimal societies and hypothesis generation through adaptation to specific contexts.

Publications

Jung J., Miller, J. H., & Page, S. E. (2025). Agent-based modeling for psychological research on social phenomena. American Psychologist. doi:10.1037/amp0001530 [PsyArXiv Preprint]
Jung, J. (2025). An Agent-Based Model of Indirect Minority Influence on Social Change (Version 1.0.0). CoMSES Computational Model Library. Retrieved from: https://www.comses.net/codebases/7136f043-2149-47c5-9540-220db008b18c/releases/1.0.0/

Handbook of Computational Social Psychology

Computational social psychology is a branch of social psychology that uses computational methods to understand the psychological mechanisms underlying social phenomena. It uses computational modeling, social simulations, and computational analysis to gain insights into how individual and group behaviors both influence and are influenced by social dynamics. While some social psychologists have long applied these methods to study small group dynamics, social influence, and interpersonal and intergroup relations, the rise of computational social science has recently expanded the scope of social psychology to explore larger-scale collective behaviors. This edited volume aims to showcase recent advancements in computational social psychology and envision future directions for the field.

Publications

Jung, J. (in progress). Handbook of Computational Social Psychology (Ed.) Edward Elgar Publishing.

* Expected to publish in May 2027

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