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An indicator of technical emergence

Author

Listed:
  • Stephen F. Carley

    (Enterprise Innovation Institute, Georgia Tech
    Search Technology, Inc)

  • Nils C. Newman

    (Intelligent Information Services Corporation
    Search Technology, Inc)

  • Alan L. Porter

    (Search Technology, Inc
    Georgia Tech)

  • Jon G. Garner

    (Search Technology, Inc)

Abstract

Developing useful intelligence on scientific and technological emergence challenges those who would manage R&D portfolios, assess research programs, or manage innovation. Recently, the U.S. Intelligence Advanced Research Projects Activity Foresight and Understanding from Scientific Exposition Program has explored means to detect emergence via text analyses. We have been involved in positing conceptual bases for emergence, framing candidate indicators, and devising implementations. We now present a software script to generate a family of Emergence Indicators for a topic of interest. This paper offers some background, then discusses the development of this script through iterative rounds of testing, and then offers example findings. Results point to promising and actionable intelligence for R&D decision-makers.

Suggested Citation

  • Stephen F. Carley & Nils C. Newman & Alan L. Porter & Jon G. Garner, 2018. "An indicator of technical emergence," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(1), pages 35-49, April.
  • Handle: RePEc:spr:scient:v:115:y:2018:i:1:d:10.1007_s11192-018-2654-5
    DOI: 10.1007/s11192-018-2654-5
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    References listed on IDEAS

    as
    1. Lu An & Xia Lin & Chuanming Yu & Xinwen Zhang, 2015. "Measuring and visualizing the contributions of Chinese and American LIS research institutions to emerging themes and salient themes," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 1605-1634, December.
    2. Sanjay K. Arora & Alan L. Porter & Jan Youtie & Philip Shapira, 2013. "Capturing new developments in an emerging technology: an updated search strategy for identifying nanotechnology research outputs," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(1), pages 351-370, April.
    3. Stephen F. Carley & Nils C. Newman & Alan L. Porter & Jon G. Garner, 2017. "A measure of staying power: Is the persistence of emergent concepts more significantly influenced by technical domain or scale?," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 2077-2087, June.
    4. Small, Henry & Boyack, Kevin W. & Klavans, Richard, 2014. "Identifying emerging topics in science and technology," Research Policy, Elsevier, vol. 43(8), pages 1450-1467.
    5. Rotolo, Daniele & Hicks, Diana & Martin, Ben R., 2015. "What is an emerging technology?," Research Policy, Elsevier, vol. 44(10), pages 1827-1843.
    6. Zhang, Yi & Porter, Alan L. & Hu, Zhengyin & Guo, Ying & Newman, Nils C., 2014. "“Term clumping” for technical intelligence: A case study on dye-sensitized solar cells," Technological Forecasting and Social Change, Elsevier, vol. 85(C), pages 26-39.
    7. Yi Zhang & Xiao Zhou & Alan L. Porter & Jose M. Vicente Gomila & An Yan, 2014. "Triple Helix innovation in China’s dye-sensitized solar cell industry: hybrid methods with semantic TRIZ and technology roadmapping," Scientometrics, Springer;Akadémiai Kiadó, vol. 99(1), pages 55-75, April.
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