Study on the Identification of Disruptive Technology, Evidence from Nano Science

Kong, Yunhong; Huang, Biao; Wang, Yajun; Peng, Guochao

doi:10.1007/978-3-031-34668-2_6

Lecture Notes in Computer Science

2023

DOI: 10.1007/978-3-031-34668-2_6

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Study on the Identification of Disruptive Technology, Evidence from Nano Science

Yunhong Kong

Biao Huang

Yajun Wang

et al.

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Cited by 2 publications

References 37 publications

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What do we know about the disruption index in scientometrics? An overview of the literature

Leibel,

Bornmann

2023

Scientometrics

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The purpose of this paper is to provide a review of the literature on the original disruption index (DI1) and its variants in scientometrics. The DI1 has received much media attention and prompted a public debate about science policy implications, since a study published in Nature found that papers in all disciplines and patents are becoming less disruptive over time. This review explains in the first part the DI1 and its variants in detail by examining their technical and theoretical properties. The remaining parts of the review are devoted to studies that examine the validity and the limitations of the indices. Particular focus is placed on (1) possible biases that affect disruption indices (2) the convergent and predictive validity of disruption scores, and (3) the comparative performance of the DI1 and its variants. The review shows that, while the literature on convergent validity is not entirely conclusive, it is clear that some modified index variants, in particular DI5, show higher degrees of convergent validity than DI1. The literature draws attention to the fact that (some) disruption indices suffer from inconsistency, time-sensitive biases, and several data-induced biases. The limitations of disruption indices are highlighted and best practice guidelines are provided. The review encourages users of the index to inform about the variety of DI1 variants and to apply the most appropriate variant. More research on the validity of disruption scores as well as a more precise understanding of disruption as a theoretical construct is needed before the indices can be used in the research evaluation practice.

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What do we know about the disruption index in scientometrics? An overview of the literature

Leibel,

Bornmann

2023

Scientometrics

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Dimensions: Calculating disruption indices at scale

Sixt,

Pasin

2024

Quantitative Science Studies

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Assessing the disruptive nature of a line of research is a new area of academic evaluation that moves beyond standard citation-based metrics by taking into account the broader citation context of publications or patents. The “CD index” and a number of related indicators have been proposed in order to characterize the disruptiveness of scientific publications or patents. This research area has generated a lot of attention in recent years, yet there is no general consensus on the significance and reliability of disruption indices. More experimentation and evaluation would be desirable, but it is hampered by the fact that the calculation of these indicators is time-consuming, especially if done at scale on large citation networks. We present a novel SQL-based method to calculate disruption indices for the Dimensions publications data on Google BigQuery. This reduces the computational time taken to produce such indices by an order of magnitude, as well as making available such functionalities within an online environment that requires no setup efforts. We explain the novel algorithm and describe how its results align with preexisting implementations of disruption indicators. This method will enable researchers to develop, validate, and improve disruption models more quickly and with more precision.

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Study on the Identification of Disruptive Technology, Evidence from Nano Science

Cited by 2 publications

References 37 publications

What do we know about the disruption index in scientometrics? An overview of the literature

What do we know about the disruption index in scientometrics? An overview of the literature

Dimensions: Calculating disruption indices at scale

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