Generating Multidimensional Social Network to Simulate the Propagation of Information

Forestier, Mathilde; Bergier, Jean-Yves; Bouanan, Youssef; Ribault, Judicaël; Zacharewicz, Grégory; Vallespir, Bruno; Faucher, Colette

doi:10.1145/2808797.2808870

Cited by 10 publications

(10 citation statements)

References 27 publications

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“…Some algorithms based on this research have already been created [12]. The next step will be to refine them and to get a feedback from subject matter experts on the generated population.…”

Section: Discussionmentioning

confidence: 99%

Capturing Sub-Saharan African Sociality in Social Networks to Generate a Culturally Realistic Population

Faucher

Bergier

Forestier

2015

2015 International Conference on Culture and Computing (Culture Computing)

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Choosing to Design a decision support system aimed at developing the user's intercultural communication skills by making him experiment with the planning, sending and spreading of messages and their effects is particularly challenging: if the propagation process is to be realistic and accurate, it is necessary to create a virtual population represented by a network encapsulating specific cultural features. The goal of this paper is to propose a way of capturing a socio-cultural context by the study of the specific forms of sociality of the chosen people and how these forms organize their society. It allows to determine the relevant network layers (dimensions) and ultimately to generate a multidimensional social network representing a realistic population. The chosen context here is sub-Saharan Africa, with the additional requirement of simulating societies of failed, failing and war torn States, the intended user being a member of a peacekeeping force.

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“…Some algorithms based on this research have already been created [12]. The next step will be to refine them and to get a feedback from subject matter experts on the generated population.…”

Section: Discussionmentioning

confidence: 99%

Capturing Sub-Saharan African Sociality in Social Networks to Generate a Culturally Realistic Population

Faucher

Bergier

Forestier

2015

2015 International Conference on Culture and Computing (Culture Computing)

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“…A network or graph represents all relations between individuals. The algorithms used to generate the population taking into account the socio-cultural characteristics and several type of links between individuals are discussed by Forestier et al 6 We opt for the storage of information in a database so that each experiment is easily accessible and re-playable. The repository contains all the models available to execute the simulations, that is, all the servers and proxies that are used by the Executive model to produce the simulation model.…”

Section: Architecturementioning

confidence: 99%

“…5 In the context of this project, we developed a tool used to generate an artificial population (creating the nodes and the network) based on the actual socio-demographic data and depending on the study specification level. 6 Modeling population needs understanding of the specific norms and ways the society organizes itself. As instance, an Eastern European society does not have the same features as an Asian, Western Europe, or African one.…”

Section: Introductionmentioning

confidence: 99%

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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

et al. 2018

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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.

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“…Simulation is used to show that the topology of the network can affect the result of the diffusion process. In more details, a population of 350 agents has been generated according to social science population structure rules described in [23] and connected on three layers: family, friends and neighbors. These three layers represent the primary groups defined in [24].…”

Section: Overviewmentioning

confidence: 99%

DEVS based Network: Modeling and Simulation of Propagation Processes in a Multi-Layers Network

2016

Modeling and Simulation of Complexity in Intelligent, Adaptive and Autonomous Systems 2016 (MSCIAAS 2016) and Space Simulation

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This paper deals with diffusion process in a multi-layer network using DEVS (Discrete Event System Specification) formalism. Social interaction plays an important role in studying the propagation of information, innovation, ideas, and influence among its members. When an informational event appears it can either die out quickly or makes significant inroads into a population. Network diffusion process allows us to understand the dynamics and the propagation of information in Social Network (SN). These networks can consist of individuals, group of person or organizations. The interactions could be done by physical proximity contact, remote collaboration, any types of social meetings and some forms of verbal or written communication depending on the situations. In our work we use the DEVS formalism, extended by DS-DEVS and PDEVS in order to set to simulate the propagation phenomena within a multi-layer social network (MSN). The network agent behavior is represented in the form of atomic models or coupled models if they are complex, and the social network is managed using DS-DEVS.

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Generating Multidimensional Social Network to Simulate the Propagation of Information

Cited by 10 publications

References 27 publications

Capturing Sub-Saharan African Sociality in Social Networks to Generate a Culturally Realistic Population

Capturing Sub-Saharan African Sociality in Social Networks to Generate a Culturally Realistic Population

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

DEVS based Network: Modeling and Simulation of Propagation Processes in a Multi-Layers Network

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