College of Engineering, IT & Environment, Charles Darwin University, Casuarina, Northern Territory, Australia.
College of Computing & Informatics, Drexel University, Philadelphia, PA, United States of America.
PLoS One. 2021 Aug 11;16(8):e0254744. doi: 10.1371/journal.pone.0254744. eCollection 2021.
The breakthrough potentials of research papers can be explained by their boundary-spanning qualities. Here, for the first time, we apply the structural variation analysis (SVA) model and its affiliated metrics to investigate the extent to which such qualities characterize a group of Nobel Prize winning papers. We find that these papers share remarkable boundary-spanning traits, marked by exceptional abilities to connect disparate and topically-diverse clusters of research papers. Further, their publications exert structural variations on a scale that significantly alters the betweenness centrality distributions in existing intellectual space. Overall, SVA not only provides a set of leading indicators for describing future Nobel Prize winning papers, but also broadens our understanding of similar prize-winning properties that may have been overlooked among other regular publications.
研究论文的突破潜力可以通过其跨越边界的特性来解释。在这里，我们首次应用结构变异分析（SVA）模型及其相关指标来研究这些特性在多大程度上可以描述一组诺贝尔奖获奖论文。我们发现，这些论文具有显著的跨越边界的特征，能够将不同的、主题多样的研究论文集群连接起来。此外，它们的出版物在结构上产生了变化，这种变化显著改变了现有知识空间中的中间中心度分布。总的来说，SVA 不仅提供了一组描述未来诺贝尔奖获奖论文的领先指标，而且拓宽了我们对其他常规出版物中可能被忽视的类似获奖特性的理解。
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