COMPUTATIONAL SOCIAL SCIENCE

Department of Computational Social Science Seminar Abstract

Friday, April 5 - 3:00 p.m.
Center for Social Complexity Suite
Research Hall, 3rd Floor

TBA

Hugh McFarlane
CSS PhD Student
George Mason University

Abstract: This presentation describes a preliminary framework for modeling how resilience in political systems develops. The long-term goal is to improve probabilistic forecasting of changes to political institutions in response to crises. Over the last decade, political developments in the Middle East and Eastern Europe illustrate the punctuated equilibrium pattern that characterizes the onset of institutional change. Understanding the complex multi-scale dynamics behind these transitions is a critical component of decision-making by national level policy makers and a wide range of groups in the public and private sectors. Shifts in the composition and character of political institutions demands alterations to political strategies, introduces new actors and removes status quo actors from power thus reshaping exchange networks. Consequently, the resilience of the system can be described as an emergent property of the interaction of various individual actors pursuing survival strategies that eventually coalesce around a satisfactory set of institutions. Accurately modeling this process offers analysts a framework to assess the impacts of various shocks to the system. This presentation reviews a statistical analysis of the duration of institutional characteristics in states over the last 210 years. Hazard rate and survival analysis indicate that there are underlying dynamics common to a wide range of political systems that drive resilience. The structure of an agent-based model of political resilience is developed that integrates these statistical insights. The political transitions in Kenya from 1989-1992 and 2008-2010 are presented as an illustrative case of this approach.