MODELING HISTORICAL PROCESSES: METHODS, APPROACHES, AND PROSPECTS
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Abstract
The modeling of historical processes has become an increasingly important methodological approach in modern historical research. By applying mathematical, statistical, and computational models, historians are able to analyze complex social, political, economic, and cultural dynamics across time. Historical modeling allows researchers to identify patterns, test hypotheses, and simulate alternative historical scenarios that are difficult to observe through traditional narrative methods alone. This article explores the concept of historical process modeling, its main approaches, methodological tools, advantages, and limitations, as well as future prospects in the context of digital humanities.
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References
1.McClelland, P. D. (1975). Causal Explanation and Model Building in History, Economics, and the New Economic History. Cornell University Press.
2.Turchin, P. (2003). Historical Dynamics: Why States Rise and Fall. Princeton University Press.
3.Turchin, P. (2016). Ultrasociety: How 10,000 Years of War Made Humans the Greatest Cooperators on Earth. Beresta Books.
4.Goldstone, J. A. (1991). Revolution and Rebellion in the Early Modern World. University of California Press.
5.Fogel, R. W., & Engerman, S. L. (1974). Time on the Cross: The Economics of American Negro Slavery. Little, Brown and Company.
6.North, D. C. (1990). Institutions, Institutional Change and Economic Performance. Cambridge University Press.
7.Braudel, F. (1980). On History. University of Chicago Press.
8.Epstein, J. M., & Axtell, R. (1996). Growing Artificial Societies: Social Science from the Bottom Up. MIT Press.
9.Gilbert, N., & Troitzsch, K. (2005). Simulation for the Social Scientist. Open University Press.
10.Manning, P. (2013). Big Data in History. Palgrave Macmillan.
11.Bavel, B. van, & Curtis, D. R. (2016). “Better Understanding Disasters by Better Using History: Systematically Using the Historical Record as One Way to Advance Research into Disasters.” International Journal of Mass Emergencies and Disasters, 34(1), 143–169.