A Sleeping Beauty (SB) in science refers to a paper whose importance is not recognized for several years after publication. Its citation history exhibits a long hibernation period followed by a sudden spike of popularity. Previous studies suggest a relative scarcity of SBs. The reliability of this conclusion is, however, heavily dependent on identification methods based on arbitrary threshold parameters for sleeping time and number of citations, applied to small or monodisciplinary bibliographic datasets. Here we present a systematic, large-scale, and multidisciplinary analysis of the SB phenomenon in science. We introduce a parameter-free measure that quantifies the extent to which a specific paper can be considered an SB. We apply our method to 22 million scientific papers published in all disciplines of natural and social sciences over a time span longer than a century. Our results reveal that the SB phenomenon is not exceptional. There is a continuous spectrum of delayed recognition where both the hibernation period and the awakening intensity are taken into account. Although many cases of SBs can be identified by looking at monodisciplinary bibliographic data, the SB phenomenon becomes much more apparent with the analysis of multidisciplinary datasets, where we can observe many examples of papers achieving delayed yet exceptional importance in disciplines different from those where they were originally published. Our analysis emphasizes a complex feature of citation dynamics that so far has received little attention, and also provides empirical evidence against the use of short-term citation metrics in the quantification of scientific impact.
翻译:科学中一个睡美人(SB)是指一份在出版后几年内没有被承认的重要性的论文。其引用历史表明一个长期的冬眠期,随后突然出现了受欢迎程度的急剧上升。先前的研究显示,SB的相对稀缺。然而,这一结论的可靠性在很大程度上取决于基于睡眠时间和引用次数的任意门槛参数的识别方法,适用于小型或单学科书目数据集。我们在这里对科学中SB现象进行了系统、大规模和多学科的分析。我们引入了一个无参数的计量措施,对具体文件在多大程度上可以被视为SB进行了量化。我们采用的方法,在超过一个世纪的时间里,对在自然和社会科学所有学科中发表的2,200万份科学论文都采用了我们的方法。我们的结果显示,SB现象并非例外。在将休眠期和觉醒的强度考虑在内时,人们不断有一系列的延迟认识。虽然通过研究单科书目数据可以确定SB的许多案例,但随着对多学科数据集的分析,SB现象变得非常明显。我们从中观察到了许多不同学科的精确性分析结果,从这些例子中得出了我们从这些非常不同的精确性的例子。