This paper introduces the perspective of dynamic citation process to identify citation patterns of scientific breakthroughs. We construct a series of citation metrics and apply them to over 100 pairs of Nobel and non-Nobel papers with millions of citations. As expected, we find that most metrics cannot distinguish the two groups under similar conditions of discipline, publication year, venue, and citation impact. Some metrics, however, not only show significant discriminative power, but also reflect scientific breakthroughs’ temporal and structural characteristics—namely, prematurity and fruitfulness. Breakthrough works, that is, have long-lasting impact, but recognition lags behind; they do not just solve a problem, but more importantly open up new questions. Three metrics—average clustering coefficient, connectivity, and density of citing literature networks—show particular promise for early identification of breakthrough works. Our findings bear significant implications for science and technology management practices: from a science policy standpoint, our work demonstrates the utility of this citation process-based approach and provides a new dimension for both innovation researchers and decision makers in search of emerging scientific breakthroughs.

本文介绍了动态引证过程的观点，以确定科学突破的引证模式。我们构建了一系列引文指标，并将其应用于100多对具有数百万次引文的诺贝尔和非诺贝尔论文。不出所料，我们发现大多数指标无法在相似的纪律，出版年份，地点和引文影响条件下区分两组。但是，某些指标不仅显示出显着的判别力，而且还反映出科学突破的时空和结构特征，即过早成熟和富有成果。突破性的工作具有长远的影响，但认可却滞后；他们不仅解决问题，更重要的是提出新的问题。三个指标引用文献网络的平均聚类系数，连通性和密度，显示出对早期发现突破性作品的特别希望。我们的发现对科学技术管理实践具有重大意义：从科学政策的角度来看，我们的工作证明了这种基于引文过程的方法的实用性，并为创新研究人员和决策者提供了新的维度，以寻求新兴的科学突破。