Modeling and Simulation of Human Reaction in a Multidimensional Social Network

摘要

The impacts of information on individuals within a social network are, mostly, statically modeled and the dynamic is not frequently tackled. In addition, the works about modeling and simulation of the populations reactions to the information do not use explicit specification languages to describe their models. These models are specified in the shape of graph or math formulas and then directly implemented and coded using classical programming languages. We propose to model, in the frame of SICOMORES project studying stabilization phase of a conflict, the actions of influence in a multidimensional social networks (MSN). Each graph dimension corresponds to a predetermined social network (Family, religion, neighbor-hood). The purpose of this work is to provide a simple but efficient and accurate framework to model the behavior of an individual, but also the simulation of the propagation of information among a group of individuals and its influence on their behavior. In more details, we define a set of models of individuals characterized by a set of state variables (e.g. Using Maslow to construct the behavior of an individual) and the mesh between the individuals within a social network. Then, we introduce the platform architecture, sharing resources, specifically designed to simulate MSN. In the end, a scenario is used to validate our models using the platform based on DEVS formalism.