Sociological Theory Formalization with Agent-Based Modeling

Keywords: agent-based model, verbal theory, formal theory, program code


Sociologists usually use verbal theories to describe and explain the social phenomena. But formal theories also can be applied for this purpose. There are verbal theories written in formal language. In particular formal theories are important for studying complex systems. Complex systems are dynamic and their behavior changes over time. Verbal theories help us to describe the components of a complex system, their characteristics, actions and interactions but cannot catch changes in the behavior of complex system over time. Agent-based modeling is a method of theoretical analysis of complex systems. Agent-based model is a formal theory presented as a program code. It is applied to explain the behavior of complex system and require a verbal theory. We find out that the middle-range theory is a sociological theory can be presented as an agent-based model. It explains the emergence of macro-level phenomena from the actions and interactions of agents at the micro-level. The middle-range theory explains a limited range of macro-level phenomena and provides partial explanations. It consists of agents, environment and rules. We also propose the stages of middle-range theory formalization. They are relevant for cases when we implement an agent-based model in R and consider it as a function in R. The stages of middle-range theory formalization are: 1) model specification; 2) representation agents characteristics as a program code in R; 3) representation an environment as a program code in R; 4) representation rules as a program code in R; 5) creating a visualization; 6) calculation of numerical indicators; 7) detection and correction of errors in the R code. As a result we get an agent-based model and can conduct computer experiments with it.


Barbera, F. (2006). A Star is Born? The Authors, Principles and Objectives of Analytical Sociology. Papers. Revista De Sociologia, 80, 31-50.

Bruch, E., Atwell, J. (2015). Agent-Based Models in Empirical Social Research. Sociological Methods & Research, 44(2), 186-221.

De Vries, A., Meys, J. (2015). R for dummies. Chichester: Wiley.

Gilbert, N., Terna, P. (2000). How to build and use agent-based models in social science. Mind & Society, 1(1), 57-72.

Gilbert, N., Troitzsch, K. (2005). Simulation for the Social Scientist. Open University Press.

Hedström, P., Bearman, P. (2017). What Is Analytical Sociology All About? An Introductory Essay, In: P. Hedström & P. Bearman (Eds.), The Oxford Handbook of Analytical Sociology. Oxford University Press, pp. 3-24.

Hedström, P., Udehn, L. (2017). Analytical Sociology and Theories of the Middle-Range, In P. Hedström & P. Bearman (Eds.), The Oxford Handbook of Analytical Sociology. Oxford University Press, pp. 25-47.

Hedström, P., Ylikoski, P. (2010). Causal mechanisms in the social sciences. Annual Review of Sociology, 36, 49-67.

Macal, C., North, M. (2014). Introductory tutorial: Agent-based modeling and simulation. In: Proceedings of the Winter Simulation Conference 2014. IEEE, pp. 6-20.

Salgado, M., Gilbert, N. (2013). Agent-Based Modeling. In: T. Teo (Ed.), Handbook of Quantitative Methods for Educational Research. Sense Publishers, pp. 247-265.

Smaldino, P. (2017). Models are stupid, and we need more of them. In: R. Vallacher, A. Nowak, & S. Read (Eds.), Computational Social Psychology, pp. 311-331. Routledge.

Smaldino, P. (2020). How to translate a verbal theory into a formal model. Social Psychology, 51(4), 207-218.

Squazzoni, F. (2012). Agent-Based Computational Sociology. J. Wiley & Sons.