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Modeling and Simulation of Human Reaction in a Multidimensional Social Network

机译：多维社会网络中人类反应的建模与仿真

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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, neighborhood). 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.
机译：信息对社交网络中个人的影响大多是静态模型化的，动态性并不经常得到解决。此外，有关种群对信息反应的建模和仿真的工作并未使用明确的规范语言来描述其模型。这些模型以图形或数学公式的形式指定，然后使用经典编程语言直接实现和编码。我们建议在研究冲突稳定阶段的SICOMORES项目框架中对多维社会网络（MSN）中的影响行为建模。每个图维度对应于预定的社交网络（家庭，宗教，邻居）。这项工作的目的是提供一个简单而有效且准确的框架来对个人的行为进行建模，而且还可以模拟一组人之间的信息传播及其对他们的行为的影响。更详细地，我们定义了一组具有一组状态变量（例如，使用马斯洛（Maslow）构建个体行为）和社交网络中的个体之间的网格的个体模型。然后，我们介绍平台架构，共享资源，这些资源是专门为模拟MSN设计的。最后，使用一个场景使用基于DEVS形式主义的平台来验证我们的模型。

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