COMPUTATIONAL SOCIAL SCIENCE – Towards an ABM for Civil Revolution: Modeling Emergence of Protesters, Military Decisions, and Resulting State of the Institution – Salwa Ismail
COMPUTATIONAL SOCIAL SCIENCE FRIDAY SEMINAR
Salwa Ismail, PhD Student
Computational Social Science
Department of Computational and Data Sciences
George Mason University
Towards an ABM for Civil Revolution:
Modeling Emergence of Protesters, Military Decisions, and Resulting State of the Institution
Friday, March 3, 3:00-4:30 p.m.
Center for Social Complexity Suite
Research Hall, 3rd Floor
The recent string of events in the Middle East, dubbed as Arab Spring transcended rapidly. There was no mechanism to predict them or their outcome. While there are a few models that forecast rebellion, most of them do not take into account the ability of different factors, such as emotional threshold, of both the citizens and military and their the ability to be influenced by vision of what is going around the agent geographically, along with the influence of media/communication channels, to form a realm of influence and affect the actions of the agents simultaneously. This paper explores an agent-based model whose agents react based on economic and emotional levels and a rebellion ensues. Once the rebellion has begun, there are several other factors in this agent-based model that decide the outcome of the rebellion including agents being killed, their geographic vision, their inclement towards news/media, being influenced by current events, and also their personality type of A or B; all these factors combined together affect the dynamics of the unanticipated revolution. The results of the model are rendered in a short duration of time, as one would expect of revolutions, except for those that plunder into a civil war state. The model could be used as one of many components for forecasting future rebellions that have a combination of factors present, as those discussed this paper.
This session will be live-streamed on the newly created CSS program YouTube channel.