Network modularity controls the speed of information diffusion,Physical Review E

当前位置： X-MOL 学术 › Phys. Rev. E › 论文详情

Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)

Network modularity controls the speed of information diffusion
Physical Review E ( IF 2.2 ) Pub Date : 2020-11-30 , DOI: 10.1103/physreve.102.052316
Hao Peng ₁ , Azadeh Nematzadeh ₂ , Daniel M Romero ₁ , Emilio Ferrara ₃

Affiliation

The rapid diffusion of information and the adoption of social behaviors are of critical importance in situations as diverse as collective actions, pandemic prevention, or advertising and marketing. Although the dynamics of large cascades have been extensively studied in various contexts, few have systematically examined the impact of network topology on the efficiency of information diffusion. Here, by employing the linear threshold model on networks with communities, we demonstrate that a prominent network feature—the modular structure—strongly affects the speed of information diffusion in complex contagion. Our simulations show that there always exists an optimal network modularity for the most efficient spreading process. Beyond this critical value, either a stronger or a weaker modular structure actually hinders the diffusion speed. These results are confirmed by an analytical approximation. We further demonstrate that the optimal modularity varies with both the seed size and the target cascade size and is ultimately dependent on the network under investigation. We underscore the importance of our findings in applications from marketing to epidemiology, from neuroscience to engineering, where the understanding of the structural design of complex systems focuses on the efficiency of information propagation.

中文翻译：

网络模块化控制信息传播的速度

信息的快速传播和社会行为的采用在集体行动、流行病预防或广告和营销等多种情况下至关重要。尽管大型级联的动力学已在各种背景下得到广泛研究，但很少有人系统地研究网络拓扑对信息传播效率的影响。在这里，通过在社区网络上采用线性阈值模型，我们证明了一个突出的网络特征——模块化结构——强烈影响复杂传染中信息传播的速度。我们的模拟表明，对于最有效的传播过程，始终存在最佳的网络模块化。超过这个临界值，更强或更弱的模块化结构实际上都会阻碍扩散速度。这些结果通过分析近似得到证实。我们进一步证明，最佳模块化随着种子大小和目标级联大小的变化而变化，并且最终取决于所研究的网络。我们强调我们的发现在从营销到流行病学、从神经科学到工程学的应用中的重要性，其中对复杂系统结构设计的理解侧重于信息传播的效率。

更新日期：2020-12-01

点击分享查看原文

点击收藏

公开下载

阅读更多本刊最新论文本刊介绍/投稿指南11