Discrete Event System Specification-based framework for modeling and simulation of propagation phenomena in social networks: application to the information spreading in a multi-layer social network. (May 2019)

• Record Type: Journal Article
• Authors: Bouanan, Youssef; Zacharewicz, Gregory; Ribault, Judicael; Vallespir, Bruno
• Is Part Of: Simulation. Volume 95:Number 5(2019)
• Page Start: 411
• Page End: 427
• Publication Date: 2019-05
• Subjects: Formal modeling -- simulation -- Discrete Event System Specification formalism -- modeling and predicting information diffusion -- information propagation -- social network; Computer simulation -- Periodicals; 003.3
• DOI: 10.1177/0037549718776368
• Languages: English
• ISSNs: 0037-5497

Abstract

The diffusion of information is defined as the communication process by which an idea or information spreads within a social system and impacts the behavior of social actors (individuals). The social interaction plays an important role in studying the propagation of information and how it influences people. When an informational event occurs, it can either die out quickly or have significant impact on a population. The interactions could be supported by physical proximity contact, remote collaboration, any type of social meetings, and some forms of verbal or written communication, depending on the situations. Institutions and firms search to understand and predict the impact of information propagation on individuals. Agent-based modeling is a powerful approach for studying such a collective process. However, existing models oversimplify the cultural attributes, the different types of links, and information content, despite the evidence of their central role in the diffusion process. In this context, great benefits could be derived from the exploitation of an individual's personality and cultural values in the diffusion models. In this paper, we describe a new architecture for an agent-based model using the DEVS (Discrete Event System Specification) framework and show how this architecture is flexible and can support the simulation of the dissemination process. In more detail, we define a set of models of individuals characterized by a set of state variables to represent the behavior of an individual and the individual's network within a multi-layer social network. Then, we start by introducing the platform architecture, specifically designed to simulate message propagation in a multi-layer network. Finally, a military scenario of message diffusion during a stabilization phase is used to test our DEVS models on the platform and the relevancy of the simulation results.