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An advanced diffusion model to identify emergent research issues: the case of optoelectronic devices

Author

Listed:
  • Edgar Schiebel

    (AIT Austrian Institute of Technology GmbH, Tech Gate Vienna)

  • Marianne Hörlesberger

    (AIT Austrian Institute of Technology GmbH, Tech Gate Vienna)

  • Ivana Roche

    (INIST-CNRS)

  • Claire François

    (INIST-CNRS)

  • Dominique Besagni

    (INIST-CNRS)

Abstract

Scientific progress in technology oriented research fields is made by incremental or fundamental inventions concerning natural science effects, materials, methods, tools and applications. Therefore our approach focuses on research activities of such technological elements on the basis of keywords in published articles. In this paper we show how emerging topics in the field of optoelectronic devices based on scientific literature data from the PASCAL-database can be identified. We use Results from PROMTECH project, whose principal objective was to produce a methodology allowing the identification of promising emerging technologies. In this project, the study of the intersection of Applied Sciences as well as Life (Biological & Medical) Sciences domains and Physics with bibliometric methods produced 45 candidate technological fields and the validation by expert panels led to a final selection of 10 most promising ones. These 45 technologies were used as reference fields. In order to detect the emerging research, we combine two methodological approaches. The first one introduces a new modelling of field terminology evolution based on bibliometric indicators: the diffusion model and the second one is a diachronic cluster analysis. With the diffusion model we identified single keywords that represent a high dynamic of the mentioned technology elements. The cluster analysis was used to recombine articles, where the identified keywords were used to technological topics in the field of optoelectronic devices. This methodology allows us to answer the following questions: Which technological aspects within our considered field can be detected? Which of them are already established and which of them are new? How are the topics linked to each other?

Suggested Citation

  • Edgar Schiebel & Marianne Hörlesberger & Ivana Roche & Claire François & Dominique Besagni, 2010. "An advanced diffusion model to identify emergent research issues: the case of optoelectronic devices," Scientometrics, Springer;Akadémiai Kiadó, vol. 83(3), pages 765-781, June.
    • Handle: RePEc:spr:scient:v:83:y:2010:i:3:d:10.1007_s11192-009-0137-4
    DOI: 10.1007/s11192-009-0137-4
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    References listed on IDEAS

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    1. Mogoutov, Andrei & Cambrosio, Alberto & Keating, Peter & Mustar, Philippe, 2008. "Biomedical innovation at the laboratory, clinical and commercial interface: A new method for mapping research projects, publications and patents in the field of microarrays," Journal of Informetrics, Elsevier, vol. 2(4), pages 341-353.
    2. Mogoutov, Andrei & Kahane, Bernard, 2007. "Data search strategy for science and technology emergence: A scalable and evolutionary query for nanotechnology tracking," Research Policy, Elsevier, vol. 36(6), pages 893-903, July.
    3. F. W. Lancaster & Ja‐Lih Lee, 1985. "Bibliometric techniques applied to issues management: A case study," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 36(6), pages 389-397, November.
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    Cited by:

    1. Marianne Hörlesberger & Ivana Roche & Dominique Besagni & Thomas Scherngell & Claire François & Pascal Cuxac & Edgar Schiebel & Michel Zitt & Dirk Holste, 2013. "A concept for inferring ‘frontier research’ in grant proposals," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(2), pages 129-148, November.
    2. Xiaoguang Wang & Qikai Cheng & Wei Lu, 2014. "Analyzing evolution of research topics with NEViewer: a new method based on dynamic co-word networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(2), pages 1253-1271, November.
    3. Yuan Zhou & Heng Lin & Yufei Liu & Wei Ding, 2019. "A novel method to identify emerging technologies using a semi-supervised topic clustering model: a case of 3D printing industry," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(1), pages 167-185, July.
    4. Jean-Charles Lamirel, 2012. "A new approach for automatizing the analysis of research topics dynamics: application to optoelectronics research," Scientometrics, Springer;Akadémiai Kiadó, vol. 93(1), pages 151-166, October.
    5. Kwon, Seokbeom & Liu, Xiaoyu & Porter, Alan L. & Youtie, Jan, 2019. "Research addressing emerging technological ideas has greater scientific impact," Research Policy, Elsevier, vol. 48(9), pages 1-1.

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