Many theories of scientific and technological progress imagine science as an iterative, developmental process periodically interrupted by innovations which disrupt and restructure the status quo. Due to the immense societal value created by these disruptive scientific and technological innovations, accurately operationalizing this perspective into quantifiable terms represents a key challenge for researchers seeking to understand the history and mechanisms underlying scientific and technological progress. Researchers have recently proposed a number of quantitative measures that seek to quantify the extent to which works in science and technology are disruptive with respect to their scientific context. While these disruption measures show promise in their ability to quantify potentially disruptive works of science and technology, their definitions are bespoke to the science of science and lack a broader theoretical framework, obscuring their interrelationships and limiting their adoption within broader network science paradigms. We propose a mathematical framework for conceptualizing and measuring disruptive scientific contributions within citation networks through the lens of network centrality, and formally relate the CD Index disruption measure and its variants to betweenness centrality. By reinterpreting disruption through the lens of centrality, we unify a number of existing citation-based disruption measures while simultaneously providing natural generalizations which enjoy empirical and computational efficiencies. We validate these theoretical observations by computing a variety of disruption measures on real citation data and find that computing these centrality-based disruption measures over ego networks of increasing radius results in better discernment of award-winning scientific innovations relative to conventional disruption metrics which rely on local citation context alone.

翻译：许多关于科学与技术进步的理论，将科学描述为一个迭代、发展的过程，期间不时被颠覆并重构现状的创新所打断。鉴于这些颠覆性的科技创见所创造的巨大社会价值，将这种视角精准地转化为可量化指标，对于试图理解科学技术进步历史与机制的研究者而言，是一项关键挑战。研究者近期提出了若干定量指标，旨在量化科技文献在其科学语境中的颠覆性程度。尽管这些颠覆性指标在量化潜在颠覆性科技作品方面展现出潜力，但其定义是针对科学学量身定制的，缺乏更广泛的理论框架，这模糊了它们之间的相互关系，并限制了其在更广泛的网络科学范式中的采纳。我们提出了一个通过网络中心性视角，在引文网络中概念化并衡量颠覆性科学贡献的数学框架，并正式将CD指数颠覆性度量及其变体与中介中心性联系起来。通过从中心性的角度重新诠释颠覆性概念，我们统一了多个现有的基于引文的颠覆性度量，同时提供了在实证与计算上均具效率的自然推广。我们通过在真实引文数据上计算多种颠覆性度量来验证这些理论观察，并发现：与仅依赖局部引文上下文的传统颠覆性指标相比，在日益扩径的自我中心网络上计算这些基于中心性的颠覆性度量，能更有效地识别出获奖科学创新。