.png){kind=icon}
返回
Social contagion models on hypergraphs
.png){kind=icon}
OA
AI
DOI：10.1103/PhysRevResearch.2.023032.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Our understanding of the dynamics of complex networked systems has increased significantly in the last two decades. However, most of our knowledge is built upon assuming pairwise relations among the system's components. This is often an oversimplification, for instance, in social interactions that occur frequently within groups. To overcome this limitation, here we study the dynamics of social contagion on hypergraphs. We develop an analytical framework and provide numerical results for arbitrary hypergraphs, which we also support with Monte Carlo simulations. Our analyses show that the model has a vast parameter space, with first- and second-order transitions, bistability, and hysteresis. Phenomenologically, we also extend the concept of latent heat to social contexts, which might help understanding oscillatory social behaviors. Our work unfolds the research line of higher-order models and the analytical treatment of hypergraphs, posing new questions and paving the way for modeling dynamical processes on higher-order structures.
Keyword:
NETWORKS
SPREAD
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
4.2
论文数:
7.6K
被引数:
2.7W
机构
引用论文
Modeling the worldwide spread of pandemic influenza: Baseline case and containment interventions.png)
PLOS MEDICINEOAAI
PLOS MEDICINEIF9.9
OAAI分享收藏Real-time numerical forecast of global epidemic spreading: case study of 2009 A/H1N1pdmBMC MEDICINEOAAI
BMC MEDICINEIF8.3
OAAI分享收藏分享收藏
查看更多内容