报告题目：Directionality Reduces the Impact of Epidemics in Multilayer Networks

报告摘要：

The study of how diseases spread has greatly benefited from advances in network modeling. Recently, a class of networks known as multilayer graphs have been shown to describe more accurately many real systems, making it possible to address more complex scenarios in epidemiology such as the interaction between different pathogens or multiple strains of the same disease. In this work, we study in depth a class of networks that have gone unnoticed up to now, despite of its relevance for spreading dynamics. Specifically, we focus on directed multilayer networks, characterized by the existence of directed links, either within the layers or across layers. Using the generating function approach and numerical simulations of a stochastic susceptible-infected-susceptible (SIS) model, we calculate the epidemic threshold for a real-world multilayer network composed by users of two different social platforms: friendfeed and twitter. Besides, we analyze several combinations of directionality: (i) Directed layer - Undirected interlinks - Directed interlinks (DUD); (ii) Directed layer - Directed interlinks - Directed layer (DDD); (iii) Undirected layer -Directed interlinks - Undirected layer (UDU), and the standard scenario for the sake of comparison, namely, (iv) Undirected layer - Undirected interlinks - Undirected layer (UUU). Our results show that the main feature that determines the value of the epidemic threshold is the directionality of the links connecting different layers. Our findings are of utmost interest given the ubiquitous presence of directed multilayer networks and the  widespread use of disease-like spreading processes in a broad range of phenomena such as diffusion processes in social and transportation systems.

报告人：王向荣 副研究员

报告人简介：王向荣博士，现在为南方科技大学副研究员。2012年10月至2016年12月，于荷兰代尔夫特理工大学取得博士学位，就读于电气工程数学计算机科学学院（Faculty of Electrical Engineering, Mathematics and Computer Science, EEMCS），师从网络科学领域著名专家Piet Van Mieghem教授。2017年3月至2018年11月，从事博士后研究，师从网络科学领域顶级专家Yamir Moreno教授。主要研究方向为网络科学，数据科学，网络鲁棒性，非线性动力学，网络频谱理论等。以第一作者发表论文12篇，包括New Journal of Physics, Physical Review E等。

时间：2019年10月29日 上午9:30

地点：中心校区知新楼B座1032报告厅

邀请人：王光辉  数学学院教授