Identifying Scientific and Technical “Unicorns”

doi:10.2478/jdis-2021-0002

Abstract

Abstract: Purpose: Using the metaphor of “unicorn,” we identify the scientific papers and technical patents characterized by the informetric feature of very high citations in the first ten years after publishing, which may provide a new pattern to understand very high impact works in science and technology.
Design/methodology/approach: When we set CT as the total citations of papers or patents in the first ten years after publication, with C_T≥ 5,000 for scientific “unicorn” and C_T≥ 500 for technical “unicorn,” we have an absolute standard for identifying scientific and technical “unicorn” publications.
Findings: We identify 165 scientific “unicorns” in 14,301,875 WoS papers and 224 technical “unicorns” in 13,728,950 DII patents during 2001–2012. About 50% of “unicorns” belong to biomedicine, in which selected cases are individually discussed. The rare “unicorns” increase following linear model, the fitting data show 95% confidence with the RMSE of scientific “unicorn” is 0.2127 while the RMSE of technical “unicorn” is 0.0923.
Research limitations: A “unicorn” is a pure quantitative consideration without concerning its quality, and “potential unicorns” as C_T≤5,000 for papers and C_T≤500 for patents are left in future studies.
Practical implications: Scientific and technical “unicorns” provide a new pattern to understand high-impact works in science and technology. The “unicorn” pattern supplies a concise approach to identify very high-impact scientific papers and technical patents.
Originality/value: The “unicorn” pattern supplies a concise approach to identify very high impact scientific papers and technical patents.

Key words: Unicorn, Scientific paper, Technical patent, Citation analysis, Patent analysis

Lucy L. Xu, Miao Qi, Fred Y. Ye. "Identifying Scientific and Technical “Unicorns”." Journal of Data and Information Science(2020). 10.2478/jdis-2021-0002

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