使用Graphlet谱图进行病毒研究协作网络的时间模式分析
Using Graphlet Spectrograms for Temporal Pattern Analysis of Virus-Research Collaboration Networks
摘要：
本文提出了一种新的科学合作网络时间模式分析方法。我们特别调查了近二十年来五次流行病或大流行病爆发以及持续的COVID-19大流行中的病毒研究活动。我们的方法体现了两个创新的组成部分。第一个是一个简单的模型的时间合作网络的时间分割的出版时间和引用历史的卷积，有效地捕捉和适应合作活动在混合的时间尺度。第二个组成部分是新的使用graphlet编码拓扑结构，并检测随着时间的推移，在协作活动的变化和持久性。我们特别发现了双叉图的两个独特而普遍的作用：（1）识别三角形集群之间的桥梁;（2）量化基层作为每个协作网络的骨干。我们提出了一些有趣的模式和发现的病毒研究活动。
英文摘要：
We introduce a new method for temporal pattern analysis of scientific collaboration networks. We investigate in particular virus research activities through five epidemic or pandemic outbreaks in the recent two decades and in the ongoing pandemic with COVID-19. Our method embodies two innovative components. The first is a simple model of temporal collaboration networks with time segmented in publication time and convolved in citation history, to effectively capture and accommodate collaboration activities at mixed time scales. The second component is the novel use of graphlets to encode topological structures and to detect change and persistence in collaboration activities over time. We discover in particular two unique and universal roles of bi-fork graphlet in (1) identifying bridges among triangle clusters and (2) quantifying grassroots as the backbone of every collaboration network. We present a number of intriguing patterns and findings about the virus-research activities.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
