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Generating Indicators of Disruptive Innovation using Big Data: Can big data approaches exploit the wealth of information on the internet help in prediction of disruption relating to innovation of disruption relating to innovation

Brackin, Roger C; Jackson, Michael J; Leyshon, Andrew; Morley, Jeremy G; Jewitt, Sarah

Authors

Roger C Brackin

Michael J Jackson

Andrew Leyshon

Jeremy G Morley

SARAH JEWITT sarah.jewitt@nottingham.ac.uk
Professor of Human Geography and Development



Abstract

Technological evolution and its potential impacts are of significant interest to govern-10 ments, corporate organizations and for academic enquiry; but assessments of technology progres-11 sion are often highly subjective. This paper prototypes potential objective measures to assess tech-12 nology progression using internet-based data. These measures may help reduce the subjective na-13 ture of such assessments and, in conjunction with other techniques, reduce the uncertainty of tech-14 nology progression assessment. The paper examines one part of the technology ecosystem, namely, 15 academic research and publications. It uses analytics performed against a large body of academic 16 paper abstracts and metadata published over 20 years to propose and demonstrate candidate indi-17 cators of technology progression. Measures prototyped are: (i) overall occurrence of technologies 18 used over time in research, (ii) the fields in which this use was made; (iii) the geographic spread of 19 specific technologies within research and (iv) the clustering of technology research over time. An 20 outcome of the analysis is an ability to assess the measures of technology progression against a set 21 of inputs and a set of commentaries and forecasts made publicly in the subject area over the last 20 22 years. The potential automated indicators of research are discussed together with other indicators 23 which might help working groups in assessing technology progression using more quantitative 24 methods. 25

Citation

Brackin, R. C., Jackson, M. J., Leyshon, A., Morley, J. G., & Jewitt, S. (2022). Generating Indicators of Disruptive Innovation using Big Data: Can big data approaches exploit the wealth of information on the internet help in prediction of disruption relating to innovation of disruption relating to innovation. Future Internet, 14(11), Article 327. https://doi.org/10.3390/fi14110327

Journal Article Type Article
Acceptance Date Nov 6, 2022
Online Publication Date Nov 11, 2022
Publication Date 2022-11
Deposit Date Nov 10, 2022
Publicly Available Date Nov 10, 2022
Journal Future Internet
Publisher MDPI
Peer Reviewed Peer Reviewed
Volume 14
Issue 11
Article Number 327
DOI https://doi.org/10.3390/fi14110327
Keywords Disruptive; Innovation; Technology; Assessment; Big Data; Unified Technology Pro-26 gression Modelling
Public URL https://nottingham-repository.worktribe.com/output/13460349
Publisher URL https://www.mdpi.com/1999-5903/14/11/327

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