Mechanistic Models in Computational Social Science

TL;DR

This paper reviews the history and role of mechanistic computational models in social science, emphasizing their importance for understanding social mechanisms and fostering interdisciplinary collaboration.

Contribution

It provides a comprehensive overview of the development and significance of mechanistic models in social science, highlighting their interdisciplinary connections and future potential.

Findings

Mechanistic models have a 60-year history in social science.

They serve multiple purposes including testing scenarios and exploring phenomena.

These models bridge social and natural sciences for interdisciplinary research.

Abstract

Quantitative social science is not only about regression analysis or, in general, data inference. Computer simulations of social mechanisms have a 60-year long history. They have been used for many different purposes -- to test scenarios, test the consistency of descriptive theories (proof-of-concept models), explore emergent phenomena, forecast, etc. In this essay, we sketch these historical developments, the role of mechanistic models in the social sciences, and the influences from the natural and formal sciences. We argue that mechanistic computational models form a common ground for social and natural sciences and look forward to possible future information flow across the social-natural divide.