Quantifying scientific breakthroughs by a novel disruption indicator based on knowledge entities

Compared to previous studies that generally detect scientific breakthroughs based on citation patterns, this article proposes a knowledge entity‐based disruption indicator by quantifying the change of knowledge directly created and inspired by scientific breakthroughs to their evolutionary trajector...

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Bibliographic Details
Published in:	Journal of the Association for Information Science and Technology Vol. 74; no. 2; pp. 150 - 167
Main Authors:	Wang, Shiyun, Ma, Yaxue, Mao, Jin, Bai, Yun, Liang, Zhentao, Li, Gang
Format:	Journal Article
Language:	English
Published:	Hoboken, USA John Wiley & Sons, Inc 01.02.2023
ISSN:	2330-1635, 2330-1643
Online Access:	Get full text
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Summary:	Compared to previous studies that generally detect scientific breakthroughs based on citation patterns, this article proposes a knowledge entity‐based disruption indicator by quantifying the change of knowledge directly created and inspired by scientific breakthroughs to their evolutionary trajectories. Two groups of analytic units, including MeSH terms and their co‐occurrences, are employed independently by the indicator to measure the change of knowledge. The effectiveness of the proposed indicators was evaluated against the four datasets of scientific breakthroughs derived from four recognition trials. In terms of identifying scientific breakthroughs, the proposed disruption indicator based on MeSH co‐occurrences outperforms that based on MeSH terms and three earlier citation‐based disruption indicators. It is also shown that in our indicator, measuring the change of knowledge inspired by the focal paper in its evolutionary trajectory is a larger contributor than measuring the change created by the focal paper. Our study not only offers empirical insights into conceptual understanding of scientific breakthroughs but also provides practical disruption indicator for scientists and science management agencies searching for valuable research.
Bibliography:	Funding information National Natural Science Foundation of China, Grant/Award Numbers: 71921002, 72174154, 72204109; The Jiangsu Funding Program for Excellent Postdoctoral Talent.
ISSN:	2330-1635 2330-1643
DOI:	10.1002/asi.24719