Defining and identifying Sleeping Beauties in science

Area of Science:

• Bibliometrics
• Scientometrics
• Scientific Impact Analysis

Background:

• The concept of 'Sleeping Beauty' (SB) papers describes scientific publications initially overlooked but later gaining significant recognition.
• Previous studies suggested SBs are rare, but relied on arbitrary thresholds and limited datasets.
• The reliability of identifying SBs is challenged by methodological limitations in existing research.

Purpose of the Study:

• To systematically analyze the Sleeping Beauty phenomenon on a large, multidisciplinary scale.
• To introduce a novel, parameter-free metric for quantifying the extent of delayed recognition in scientific papers.
• To challenge the notion of SB scarcity and explore the spectrum of delayed scientific impact.

Main Methods:

• Conducted a large-scale, multidisciplinary bibliometric analysis of 22 million scientific papers.
• Applied a new parameter-free measure to identify and quantify Sleeping Beauty papers.
• Analyzed citation dynamics across natural and social sciences over more than a century.

Main Results:

• The Sleeping Beauty phenomenon is not exceptional but exists on a continuous spectrum.
• A parameter-free approach reveals a wide range of delayed recognition patterns.
• SBs become more apparent when analyzing multidisciplinary datasets, showing cross-disciplinary impact.
• Many papers achieve significant importance in fields different from their original publication discipline.

Conclusions:

• The Sleeping Beauty phenomenon is a common feature of scientific progress, not an anomaly.
• A continuous spectrum of delayed recognition exists, challenging binary classifications.
• Multidisciplinary analysis is crucial for understanding the full scope of the SB phenomenon.
• Short-term citation metrics are insufficient for accurately quantifying long-term scientific impact.