Bi-layer network analytics: A methodology for characterizing emerging general-purpose technologies

Yi Zhang, Mengjia Wu, Wen Miao, Lu Huang and Jie Lu

Journal of Informetrics, 2021, vol. 15, issue 4

Abstract: Despite the tremendous contributions bibliometrics has made to profiling technological landscapes and identifying emerging topics, reliable methods for predicting potential technological changes are still elusive. To fill this gap, we propose a methodology based on bi-layer network analytics that characterizes emerging general-purpose technologies. The framework incorporates three novel indicators that quantify a technology's technical potential and social impacts, not just in one specific technological area but in a wide range of domains. Missing links in the network are extrapolated through a refined link prediction method, and a weighted resource allocation index ranks both current technologies and their predicted evolutions to reveal candidate innovations for further empirical and/or expert analysis. A case study on information science incorporating quanlitative and qualitative validations demonstrates the methodology to be feasible and reliable. Researchers and policymakers in information science and bibliometrics should find valuable decision support from the empirical insights presented.

Keywords: Bibliometrics; Network analytics; Emerging technologies; General-purpose technologies; Information science (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:infome:v:15:y:2021:i:4:s1751157721000730

DOI: 10.1016/j.joi.2021.101202

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