5G network technology is growing fast, thus the number of devices and the traffic are likely to pose impressive challenges. A new paradigm called “Internet-of-People” (IoP) represents a valid approach to include the social aspect. Following an IoP perspective, we believe that the knowledge of social multiplex interactions and dynamics could drive more sustainable growth. By merging this with the Device-to-Device communication (D2D), we originate a new paradigm presented in this work. We propose a novel bio-inspired approach for quantifying the impact of the social multiplex structure on D2D contents’ dissemination. Through rigorous mathematical modelling, we have shaped the D2D data dissemination process as a social contagion dynamics of two co-evolving spreading processes. We weigh the dynamic interactions by including the concepts of homophily and awareness. We have measured the effect of homophily, awareness and network heterogeneity on information diffusion. The bio-inspired mechanism is evaluated through a rigorous mathematical and algorithm analysis, and a meaningful simulation. We show that this mechanism is effective in tuning network awareness and alertness, breaking the “echo chambers” effect. Through our model, we have defined and proposed the guidelines to discriminate the nature of the contents based on contents’ dissemination.

中文翻译：

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塑造和区分 D2D 内容传播的多重社会传染动力学模型

5G网络技术发展迅速，设备数量和流量可能会带来巨大挑战。一种称为“人联网”(IoP) 的新范式代表了一种包含社交方面的有效方法。从 IoP 的角度来看，我们相信社会多元互动和动态的知识可以推动更可持续的增长。通过将其与设备到设备通信 (D2D) 相结合，我们开创了这项工作中提出的新范式。我们提出了一种新的仿生方法来量化社会多元结构对 D2D 内容传播的影响。通过严格的数学建模，我们将 D2D 数据传播过程塑造为两个共同发展的传播过程的社会传染动力学。我们通过包含同质性和意识的概念来权衡动态交互。我们测量了同质性、意识和网络异质性对信息传播的影响。通过严格的数学和算法分析以及有意义的模拟来评估仿生机制。我们表明这种机制在调整网络意识和警觉性方面是有效的，打破了“回声室”效应。通过我们的模型，我们定义并提出了基于内容传播来区分内容性质的指南。我们表明这种机制在调整网络意识和警觉性方面是有效的，打破了“回声室”效应。通过我们的模型，我们定义并提出了基于内容传播来区分内容性质的指南。我们表明这种机制在调整网络意识和警觉性方面是有效的，打破了“回声室”效应。通过我们的模型，我们定义并提出了基于内容传播来区分内容性质的指南。