The Eternal-Return Model of Human Mobility and Its Impact on Information Flow

The Eternal-Return Model of Human Mobility and Its Impact on Information Flow

Martine Collard, Philippe Collard, Erick Stattner
ISBN13: 9781522528142|ISBN10: 1522528148|EISBN13: 9781522528159
DOI: 10.4018/978-1-5225-2814-2.ch015
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MLA

Collard, Martine, et al. "The Eternal-Return Model of Human Mobility and Its Impact on Information Flow." Graph Theoretic Approaches for Analyzing Large-Scale Social Networks, edited by Natarajan Meghanathan, IGI Global, 2018, pp. 241-266. https://doi.org/10.4018/978-1-5225-2814-2.ch015

APA

Collard, M., Collard, P., & Stattner, E. (2018). The Eternal-Return Model of Human Mobility and Its Impact on Information Flow. In N. Meghanathan (Ed.), Graph Theoretic Approaches for Analyzing Large-Scale Social Networks (pp. 241-266). IGI Global. https://doi.org/10.4018/978-1-5225-2814-2.ch015

Chicago

Collard, Martine, Philippe Collard, and Erick Stattner. "The Eternal-Return Model of Human Mobility and Its Impact on Information Flow." In Graph Theoretic Approaches for Analyzing Large-Scale Social Networks, edited by Natarajan Meghanathan, 241-266. Hershey, PA: IGI Global, 2018. https://doi.org/10.4018/978-1-5225-2814-2.ch015

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Abstract

Human motions determine spatial social contacts that influence the way information spreads in a population. With the Eternal-Return model, we simulate an artificial world populated by heterogeneous individuals who differ in their mobility. This mobility model is synthetic but it represents regular patterns and it integrates the principles of periodicity, circular trajectory and variable amplitude of real patterns. We use a multi-agent framework for simulation and we endow agents with simple rules on how to move around the space and how to establish proximity-contacts. We distinguish different kinds of mobile agents, from sedentary ones to travelers. To summarize the dynamics induced by mobility over time, we define the mobility-based “social proximity network” as the network of all distinct contacts between agents. Properties such as the emergence of a giant component are given insight in the process of information spreading. We have conducted simulations to understand which density threshold allows percolation on the network when the mobility is constant and when it is varying.

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