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Mapping the Evolution of Scientific Fields

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  • Mark Herrera
  • David C Roberts
  • Natali Gulbahce

Abstract

Despite the apparent cross-disciplinary interactions among scientific fields, a formal description of their evolution is lacking. Here we describe a novel approach to study the dynamics and evolution of scientific fields using a network-based analysis. We build an idea network consisting of American Physical Society Physics and Astronomy Classification Scheme (PACS) numbers as nodes representing scientific concepts. Two PACS numbers are linked if there exist publications that reference them simultaneously. We locate scientific fields using a community finding algorithm, and describe the time evolution of these fields over the course of 1985–2006. The communities we identify map to known scientific fields, and their age depends on their size and activity. We expect our approach to quantifying the evolution of ideas to be relevant for making predictions about the future of science and thus help to guide its development.

Suggested Citation

  • Mark Herrera & David C Roberts & Natali Gulbahce, 2010. "Mapping the Evolution of Scientific Fields," PLOS ONE, Public Library of Science, vol. 5(5), pages 1-6, May.
    • Handle: RePEc:plo:pone00:0010355
    DOI: 10.1371/journal.pone.0010355
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    Cited by:

    1. Chakresh Kumar Singh & Shivakumar Jolad, 2019. "Structure and evolution of Indian physics co-authorship networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(2), pages 385-406, February.
    2. Eleonora Broccardo & Maria Mazzuca & Maria Laura Frigotto, 2020. "Social impact bonds: The evolution of research and a review of the academic literature," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 27(3), pages 1316-1332, May.
    3. Hongguang Dong & Menghui Li & Ru Liu & Chensheng Wu & Jinshan Wu, 2017. "Allometric scaling in scientific fields," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(1), pages 583-594, July.
    4. 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.
    5. Wenbing Luo & Ziyan Tian & Shihu Zhong & Qinke Lyu & Mingjun Deng, 2022. "Global Evolution of Research on Sustainable Finance from 2000 to 2021: A Bibliometric Analysis on WoS Database," Sustainability, MDPI, vol. 14(15), pages 1-23, August.
    6. John McLevey & Alexander V. Graham & Reid McIlroy-Young & Pierson Browne & Kathryn S. Plaisance, 2018. "Interdisciplinarity and insularity in the diffusion of knowledge: an analysis of disciplinary boundaries between philosophy of science and the sciences," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(1), pages 331-349, October.
    7. Wynne E. Norton & Alina Lungeanu & David A. Chambers & Noshir Contractor, 2017. "Mapping the growing discipline of dissemination and implementation science in health," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(3), pages 1367-1390, September.
    8. J. A. García & Rosa Rodriguez-Sánchez & J. Fdez-Valdivia & Daniel Torres-Salinas & Francisco Herrera, 2012. "Ranking of research output of universities on the basis of the multidimensional prestige of influential fields: Spanish universities as a case of study," Scientometrics, Springer;Akadémiai Kiadó, vol. 93(3), pages 1081-1099, December.
    9. Katchanov, Yurij L. & Markova, Yulia V., 2022. "Dynamics of senses of new physics discourse: Co-keywords analysis," Journal of Informetrics, Elsevier, vol. 16(1).
    10. Sun, Xiaoling & Ding, Kun & Lin, Yuan, 2016. "Mapping the evolution of scientific fields based on cross-field authors," Journal of Informetrics, Elsevier, vol. 10(3), pages 750-761.
    11. Andrea Palmucci & Hao Liao & Andrea Napoletano & Andrea Zaccaria, 2020. "Where is your field going? A machine learning approach to study the relative motion of the domains of physics," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-16, June.
    12. Ross Gore & Saikou Diallo & Jose Padilla, 2016. "Classifying modeling and simulation as a scientific discipline," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(2), pages 615-628, November.
    13. Cena, Anna & Gagolewski, Marek & Siudem, Grzegorz & Żogała-Siudem, Barbara, 2022. "Validating citation models by proxy indices," Journal of Informetrics, Elsevier, vol. 16(2).

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