報告題目：?Directionality Reduces the Impact of Epidemics in Multilayer Networks
?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.
報告人簡介：王向榮博士，現在為南方科技大學副研究員。2012年10月至2016年12月，于荷蘭代爾夫特理工大學取得博士學位，就讀于電氣工程數學計算機科學學院（Faculty of Electrical Engineering, Mathematics and Computer Science, EEMCS），師從網絡科學領域著名專家Piet Van Mieghem教授。2017年3月至2018年11月，從事博士后研究，師從網絡科學領域頂級專家Yamir Moreno教授。主要研究方向為網絡科學，數據科學，網絡魯棒性，非線性動力學，網絡頻譜理論等。以第一作者發表論文12篇，包括New Journal of Physics, Physical Review E等。