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Emergence scoring to identify frontier R&D topics and key players

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  • Porter, Alan L.
  • Garner, Jon
  • Carley, Stephen F.
  • Newman, Nils C.

Abstract

Indicators of technological emergence promise valuable intelligence to those determining R&D priorities. We present an implemented algorithm to calculate emergence scores for topical terms from abstract record sets. We offer a family of emergence indicators deriving from those scores. Primary emergence indicators identify “hot topic” terms. We then use those to generate secondary indicators that reflect organizations, countries, or authors especially active at frontiers in a target R&D domain. We also flag abstract records (papers or patents) rich in emergent technology content, and we score research fields on relative degree of emergence. This paper presents illustrative results for example topics – Nano-Enabled Drug Delivery, Non-Linear Programming, Dye Sensitized Solar Cells, and Big Data.

Suggested Citation

  • Porter, Alan L. & Garner, Jon & Carley, Stephen F. & Newman, Nils C., 2019. "Emergence scoring to identify frontier R&D topics and key players," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 628-643.
    • Handle: RePEc:eee:tefoso:v:146:y:2019:i:c:p:628-643
    DOI: 10.1016/j.techfore.2018.04.016
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    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.
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    5. Li, Munan & Porter, Alan L. & Suominen, Arho, 2018. "Insights into relationships between disruptive technology/innovation and emerging technology: A bibliometric perspective," Technological Forecasting and Social Change, Elsevier, vol. 129(C), pages 285-296.
    6. Alan L Porter & J David Roessner & Xiao-Yin Jin & Nils C Newman, 2002. "Measuring national ‘emerging technology’ capabilities," Science and Public Policy, Oxford University Press, vol. 29(3), pages 189-200, June.
    7. Pao-Long Chang & Chao-Chan Wu & Hoang-Jyh Leu, 2010. "Using patent analyses to monitor the technological trends in an emerging field of technology: a case of carbon nanotube field emission display," Scientometrics, Springer;Akadémiai Kiadó, vol. 82(1), pages 5-19, January.
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    9. Ying Huang & Donghua Zhu & Yue Qian & Yi Zhang & Alan L. Porter & Yuqin Liu & Ying Guo, 2017. "A hybrid method to trace technology evolution pathways: a case study of 3D printing," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 185-204, April.
    10. Ying Huang & Jannik Schuehle & Alan L. Porter & Jan Youtie, 2015. "A systematic method to create search strategies for emerging technologies based on the Web of Science: illustrated for ‘Big Data’," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 2005-2022, December.
    11. 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.
    12. 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.
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    15. Janghyeok Yoon & Kwangsoo Kim, 2011. "Identifying rapidly evolving technological trends for R&D planning using SAO-based semantic patent networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 88(1), pages 213-228, July.
    16. Boon, Wouter & Moors, Ellen, 2008. "Exploring emerging technologies using metaphors - A study of orphan drugs and pharmacogenomics," Social Science & Medicine, Elsevier, vol. 66(9), pages 1915-1927, May.
    17. 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.
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    Cited by:

    1. Vicente-Gomila, J.M. & Artacho-Ramírez, M.A. & Ting, Ma & Porter, A.L., 2021. "Combining tech mining and semantic TRIZ for technology assessment: Dye-sensitized solar cell as a case," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    2. Lu, Kun & Yang, Guancan & Wang, Xue, 2022. "Topics emerged in the biomedical field and their characteristics," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    3. Park, Inchae & Triulzi, Giorgio & Magee, Christopher L., 2022. "Tracing the emergence of new technology: A comparative analysis of five technological domains," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    4. Xu, Haiyun & Winnink, Jos & Yue, Zenghui & Zhang, Huiling & Pang, Hongshen, 2021. "Multidimensional Scientometric indicators for the detection of emerging research topics," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    5. Jiang, Man & Yang, Siluo & Gao, Qiang, 2024. "Multidimensional indicators to identify emerging technologies: Perspective of technological knowledge flow," Journal of Informetrics, Elsevier, vol. 18(1).
    6. Mike Thelwall & Pardeep Sud, 2021. "Do new research issues attract more citations? A comparison between 25 Scopus subject categories," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(3), pages 269-279, March.
    7. Worasak Klongthong & Veera Muangsin & Chupun Gowanit & Nongnuj Muangsin, 2021. "A Patent Analysis to Identify Emergent Topics and Convergence Fields: A Case Study of Chitosan," Sustainability, MDPI, vol. 13(16), pages 1-28, August.
    8. Juan D. Velásquez & Lorena Cadavid & Carlos J. Franco, 2023. "Intelligence Techniques in Sustainable Energy: Analysis of a Decade of Advances," Energies, MDPI, vol. 16(19), pages 1-45, October.
    9. Li, Munan & Wang, Wenshu & Zhou, Keyu, 2021. "Exploring the technology emergence related to artificial intelligence: A perspective of coupling analyses," Technological Forecasting and Social Change, Elsevier, vol. 172(C).
    10. Xiaozan Lyu & Ping Zhou & Loet Leydesdorff, 2020. "Eco-system mapping of techno-science linkages at the level of scholarly journals and fields," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(3), pages 2037-2055, September.
    11. Chie Hoon Song, 2021. "Exploring and Predicting the Knowledge Development in the Field of Energy Storage: Evidence from the Emerging Startup Landscape," Energies, MDPI, vol. 14(18), pages 1-20, September.
    12. Peter Sjögårde & Fereshteh Didegah, 2022. "The association between topic growth and citation impact of research publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(4), pages 1903-1921, April.
    13. Chiarello, Filippo & Giordano, Vito & Spada, Irene & Barandoni, Simone & Fantoni, Gualtiero, 2024. "Future applications of generative large language models: A data-driven case study on ChatGPT," Technovation, Elsevier, vol. 133(C).
    14. Puccetti, Giovanni & Giordano, Vito & Spada, Irene & Chiarello, Filippo & Fantoni, Gualtiero, 2023. "Technology identification from patent texts: A novel named entity recognition method," Technological Forecasting and Social Change, Elsevier, vol. 186(PB).
    15. Xu, Shuo & Hao, Liyuan & Yang, Guancan & Lu, Kun & An, Xin, 2021. "A topic models based framework for detecting and forecasting emerging technologies," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
    16. Giordano, Vito & Spada, Irene & Chiarello, Filippo & Fantoni, Gualtiero, 2024. "The impact of ChatGPT on human skills: A quantitative study on twitter data," Technological Forecasting and Social Change, Elsevier, vol. 203(C).
    17. Li, Munan & Porter, Alan L. & Suominen, Arho & Burmaoglu, Serhat & Carley, Stephen, 2021. "An exploratory perspective to measure the emergence degree for a specific technology based on the philosophy of swarm intelligence," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    18. Gozuacik, Necip & Sakar, C. Okan & Ozcan, Sercan, 2023. "Technological forecasting based on estimation of word embedding matrix using LSTM networks," Technological Forecasting and Social Change, Elsevier, vol. 191(C).

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