论文标题
使用GraphLet频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
论文作者
论文摘要
我们引入了一种新方法，用于科学协作网络的时间模式分析。我们在最近的二十年中通过五次流行病或大流行疫情以及与COVID-19的持续大流行有关，特别是病毒研究活动。我们的方法体现了两个创新组件。第一个是一个简单的时间协作网络模型，其出版时间分段并在引文历史上进行了卷积，以有效地捕获和适应混合时间尺度的协作活动。第二个组成部分是图形编码拓扑结构的新颖使用，并随着时间的推移在协作活动中检测变化和持久性。我们在（1）识别三角形簇之间的桥梁和（2）将基层量化为每个协作网络的骨干方面，尤其是在（1）识别三角形簇之间的桥梁中的两个独特而普遍的角色。我们提出了许多有关病毒研究活动的有趣模式和发现。
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.
