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Coping with methods for delineating emerging fields: Nanoscience and nanotechnology as a case study

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  • Muñoz-Écija, Teresa
  • Vargas-Quesada, Benjamín
  • Chinchilla Rodríguez, Zaida

Abstract

Proper field delineation plays an important role in scientometric studies, although it is a tough task. Based on an emerging and interdisciplinary field nanoscience and nanotechnology– this paper highlights the problem of field delineation. First we review the related literature. Then, three different approaches to delineate a field of knowledge were applied at three different levels of aggregation: subject category, publication level, and journal level. Expert opinion interviews served to assess the data, and precision and recall of each approach were calculated for comparison. Our findings confirm that field delineation is a complicated issue at both the quantitative and the qualitative level, even when experts validate results.

Suggested Citation

  • Muñoz-Écija, Teresa & Vargas-Quesada, Benjamín & Chinchilla Rodríguez, Zaida, 2019. "Coping with methods for delineating emerging fields: Nanoscience and nanotechnology as a case study," Journal of Informetrics, Elsevier, vol. 13(4).
    • Handle: RePEc:eee:infome:v:13:y:2019:i:4:s1751157718305030
    DOI: 10.1016/j.joi.2019.100976
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    References listed on IDEAS

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    1. Morteza Maghrebi & Ali Abbasi & Saeid Amiri & Reza Monsefi & Ahad Harati, 2011. "A collective and abridged lexical query for delineation of nanotechnology publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 86(1), pages 15-25, January.
    2. Ludo Waltman & Nees Jan van Eck, 2012. "A new methodology for constructing a publication‐level classification system of science," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(12), pages 2378-2392, December.
    3. Antonio J. Gómez-Núñez & Benjamín Vargas-Quesada & Félix Moya-Anegón & Wolfgang Glänzel, 2011. "Improving SCImago Journal & Country Rank (SJR) subject classification through reference analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 89(3), pages 741-758, December.
    4. Kevin W. Boyack & Richard Klavans, 2010. "Co-citation analysis, bibliographic coupling, and direct citation: Which citation approach represents the research front most accurately?," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(12), pages 2389-2404, December.
    5. Ludo Waltman & Nees Jan Eck, 2012. "A new methodology for constructing a publication-level classification system of science," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(12), pages 2378-2392, December.
    6. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-856, July.
    7. Alexander I. Pudovkin & Eugene Garfield, 2002. "Algorithmic procedure for finding semantically related journals," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 53(13), pages 1113-1119, November.
    8. Shu, Fei & Julien, Charles-Antoine & Zhang, Lin & Qiu, Junping & Zhang, Jing & Larivière, Vincent, 2019. "Comparing journal and paper level classifications of science," Journal of Informetrics, Elsevier, vol. 13(1), pages 202-225.
    9. 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.
    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. Wolfgang Glänzel & András Schubert, 2003. "A new classification scheme of science fields and subfields designed for scientometric evaluation purposes," Scientometrics, Springer;Akadémiai Kiadó, vol. 56(3), pages 357-367, March.
    13. Zucker, Lynne G. & Darby, Michael R. & Furner, Jonathan & Liu, Robert C. & Ma, Hongyan, 2007. "Minerva unbound: Knowledge stocks, knowledge flows and new knowledge production," Research Policy, Elsevier, vol. 36(6), pages 850-863, July.
    14. Klavans, Richard & Boyack, Kevin W., 2017. "Research portfolio analysis and topic prominence," Journal of Informetrics, Elsevier, vol. 11(4), pages 1158-1174.
    15. Philippe Mongeon & Adèle Paul-Hus, 2016. "The journal coverage of Web of Science and Scopus: a comparative analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(1), pages 213-228, January.
    16. Kevin W. Boyack & Richard Klavans, 2010. "Co‐citation analysis, bibliographic coupling, and direct citation: Which citation approach represents the research front most accurately?," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(12), pages 2389-2404, December.
    17. Gómez-Núñez, Antonio J. & Batagelj, Vladimir & Vargas-Quesada, Benjamín & Moya-Anegón, Félix & Chinchilla-Rodríguez, Zaida, 2014. "Optimizing SCImago Journal & Country Rank classification by community detection," Journal of Informetrics, Elsevier, vol. 8(2), pages 369-383.
    18. Joachim Schummer, 2004. "Multidisciplinarity, interdisciplinarity, and patterns of research collaboration in nanoscience and nanotechnology," Scientometrics, Springer;Akadémiai Kiadó, vol. 59(3), pages 425-465, March.
    19. Can Huang & Ad Notten & Nico Rasters, 2011. "Nanoscience and technology publications and patents: a review of social science studies and search strategies," The Journal of Technology Transfer, Springer, vol. 36(2), pages 145-172, April.
    20. Michel Zitt, 2015. "Meso-level retrieval: IR-bibliometrics interplay and hybrid citation-words methods in scientific fields delineation," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(3), pages 2223-2245, March.
    21. Loet Leydesdorff & Ping Zhou, 2007. "Nanotechnology as a field of science: Its delineation in terms of journals and patents," Scientometrics, Springer;Akadémiai Kiadó, vol. 70(3), pages 693-713, March.
    22. Elise Bassecoulard & Alain Lelu & Michel Zitt, 2007. "Mapping nanosciences by citation flows: A preliminary analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 70(3), pages 859-880, March.
    23. Daniele Fanelli & Wolfgang Glänzel, 2013. "Bibliometric Evidence for a Hierarchy of the Sciences," PLOS ONE, Public Library of Science, vol. 8(6), pages 1-11, June.
    24. Nees Jan Eck & Ludo Waltman, 2010. "Software survey: VOSviewer, a computer program for bibliometric mapping," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(2), pages 523-538, August.
    25. Bruce E. Hansen, 2017. "Regression Kink With an Unknown Threshold," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(2), pages 228-240, April.
    26. Han Woo Park & Jungwon Yoon & Loet Leydesdorff, 2016. "The normalization of co-authorship networks in the bibliometric evaluation: the government stimulation programs of China and Korea," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(2), pages 1017-1036, November.
    27. Loet Leydesdorff, 2007. "Betweenness centrality as an indicator of the interdisciplinarity of scientific journals," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 58(9), pages 1303-1319, July.
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    Cited by:

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    2. Kang, Inje & Yang, Jiseong & Lee, Wonjae & Seo, Eun-Yeong & Lee, Duk Hee, 2023. "Delineating development trends of nanotechnology in the semiconductor industry: Focusing on the relationship between science and technology by employing structural topic model," Technology in Society, Elsevier, vol. 74(C).
    3. Xinyuan Zhang & Qing Xie & Chaemin Song & Min Song, 2022. "Mining the evolutionary process of knowledge through multiple relationships between keywords," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(4), pages 2023-2053, April.

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