Nonlinear Sciences – Adaptation and Self-Organizing Systems
Scientific paper
2009-07-14
Proc. 2009 IEEE Multi-conference on Systems and Control, St. Petersburg, Russia, July 2009
Nonlinear Sciences
Adaptation and Self-Organizing Systems
Scientific paper
This two-part paper presents a new approach to predictive analysis for social processes. In Part I, we begin by identifying a class of social processes which are simultaneously important in applications and difficult to predict using existing methods. It is shown that these processes can be modeled within a multi-scale, stochastic hybrid system framework that is sociologically sensible, expressive, illuminating, and amenable to formal analysis. Among other advantages, the proposed modeling framework enables proper characterization of the interplay between the intrinsic aspects of a social process (e.g., the appeal of a political movement) and the social dynamics which are its realization; this characterization is key to successful social process prediction. The utility of the modeling methodology is illustrated through a case study involving the global SARS epidemic of 2002-2003. Part II of the paper then leverages this modeling framework to develop a rigorous, computationally tractable approach to social process predictive analysis.
Colbaugh Richard
Glass Kristin
No associations
LandOfFree
Predictive Analysis for Social Processes I: Multi-Scale Hybrid System Modeling does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Predictive Analysis for Social Processes I: Multi-Scale Hybrid System Modeling, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Predictive Analysis for Social Processes I: Multi-Scale Hybrid System Modeling will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-331563