IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0233997.html
   My bibliography  Save this article

Where is your field going? A machine learning approach to study the relative motion of the domains of physics

Author

Listed:
  • Andrea Palmucci
  • Hao Liao
  • Andrea Napoletano
  • Andrea Zaccaria

Abstract

We propose an original approach to describe the scientific progress in a quantitative way. Using innovative Machine Learning techniques we create a vector representation for the PACS codes and we use them to represent the relative movements of the various domains of Physics in a multi-dimensional space. This methodology unveils about 25 years of scientific trends, enables us to predict innovative couplings of fields, and illustrates how Nobel Prize papers and APS milestones drive the future convergence of previously unrelated fields.

Suggested Citation

  • 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.
    • Handle: RePEc:plo:pone00:0233997
    DOI: 10.1371/journal.pone.0233997
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0233997
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0233997&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0233997?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. David Chavalarias & Jean-Philippe Cointet, 2013. "Phylomemetic Patterns in Science Evolution—The Rise and Fall of Scientific Fields," PLOS ONE, Public Library of Science, vol. 8(2), pages 1-11, February.
    2. 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.
    3. Cimini, Giulio & Zaccaria, Andrea & Gabrielli, Andrea, 2016. "Investigating the interplay between fundamentals of national research systems: Performance, investments and international collaborations," Journal of Informetrics, Elsevier, vol. 10(1), pages 200-211.
    4. 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.
    5. Emanuele Pugliese & Giulio Cimini & Aurelio Patelli & Andrea Zaccaria & Luciano Pietronero & Andrea Gabrielli, 2017. "Unfolding the innovation system for the development of countries: co-evolution of Science, Technology and Production," Papers 1707.05146, arXiv.org, revised Dec 2017.
    6. Ben Shneiderman, 2018. "Twin-Win Model: A human-centered approach to research success," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 115(50), pages 12590-12594, December.
    7. Yifang Ma & Brian Uzzi, 2018. "Scientific prize network predicts who pushes the boundaries of science," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 115(50), pages 12608-12615, December.
    8. Wendy Martinez, 2018. "How science and technology developments impact employment and education," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 115(50), pages 12624-12629, December.
    9. Tao Jia & Dashun Wang & Boleslaw K. Szymanski, 2017. "Quantifying patterns of research-interest evolution," Nature Human Behaviour, Nature, vol. 1(4), pages 1-7, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sabrina Aufiero & Giordano De Marzo & Angelica Sbardella & Andrea Zaccaria, 2023. "Mapping job complexity and skills into wages," Papers 2304.05251, arXiv.org.
    2. Tacchella, Andrea & Zaccaria, Andrea & Miccheli, Marco & Pietronero, Luciano, 2023. "Relatedness in the era of machine learning," Chaos, Solitons & Fractals, Elsevier, vol. 176(C).
    3. Andrea Tacchella & Andrea Zaccaria & Marco Miccheli & Luciano Pietronero, 2021. "Relatedness in the Era of Machine Learning," Papers 2103.06017, arXiv.org.
    4. Francisco Galuppo Azevedo & Fabricio Murai, 2021. "Evaluating the state-of-the-art in mapping research spaces: A Brazilian case study," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-27, March.
    5. Yu, Xiaoyao & Szymanski, Boleslaw K. & Jia, Tao, 2021. "Become a better you: Correlation between the change of research direction and the change of scientific performance," Journal of Informetrics, Elsevier, vol. 15(3).
    6. Katchanov, Yurij L. & Markova, Yulia V., 2022. "Dynamics of senses of new physics discourse: Co-keywords analysis," Journal of Informetrics, Elsevier, vol. 16(1).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sha Yuan & Zhou Shao & Xingxing Wei & Jie Tang & Wendy Hall & Yongli Wang & Ying Wang & Ye Wang, 2020. "Science behind AI: the evolution of trend, mobility, and collaboration," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(2), pages 993-1013, August.
    2. Chao Min & Qingyu Chen & Erjia Yan & Yi Bu & Jianjun Sun, 2021. "Citation cascade and the evolution of topic relevance," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(1), pages 110-127, January.
    3. Katchanov, Yurij L. & Markova, Yulia V., 2022. "Dynamics of senses of new physics discourse: Co-keywords analysis," Journal of Informetrics, Elsevier, vol. 16(1).
    4. Patelli, Aurelio & Napolitano, Lorenzo & Cimini, Giulio & Gabrielli, Andrea, 2023. "Geography of science: Competitiveness and inequality," Journal of Informetrics, Elsevier, vol. 17(1).
    5. Wenyuan Liu & Andrea Nanetti & Siew Ann Cheong, 2017. "Knowledge evolution in physics research: An analysis of bibliographic coupling networks," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-19, September.
    6. 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.
    7. 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.
    8. Luciano Pietronero & Matthieu Cristelli & Andrea Gabrielli & Dario Mazzilli & Emanuele Pugliese & Andrea Tacchella & Andrea Zaccaria, 2017. "Economic Complexity: "Buttarla in caciara" vs a constructive approach," Papers 1709.05272, arXiv.org.
    9. Yu, Shuo & Alqahtani, Fayez & Tolba, Amr & Lee, Ivan & Jia, Tao & Xia, Feng, 2022. "Collaborative Team Recognition: A Core Plus Extension Structure," Journal of Informetrics, Elsevier, vol. 16(4).
    10. Annita Nugent & Ho Fai Chan & Uwe Dulleck, 2022. "Government funding of university-industry collaboration: exploring the impact of targeted funding on university patent activity," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(1), pages 29-73, January.
    11. Hans Pohl, 2021. "Internationalisation, innovation, and academic–corporate co-publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 1329-1358, February.
    12. Rodríguez-Navarro, Alonso & Brito, Ricardo, 2018. "Technological research in the EU is less efficient than the world average. EU research policy risks Europeans’ future," Journal of Informetrics, Elsevier, vol. 12(3), pages 718-731.
    13. Loconto, Allison & Desquilbet, Marion & Moreau, Théo & Couvet, Denis & Dorin, Bruno, 2020. "The land sparing – land sharing controversy: Tracing the politics of knowledge," Land Use Policy, Elsevier, vol. 96(C).
    14. 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.
    15. Lorenzo Napolitano & Evangelos Evangelou & Emanuele Pugliese & Paolo Zeppini & Graham Room, 2017. "Technology networks: the autocatalytic origins of innovation," Papers 1708.03511, arXiv.org, revised Apr 2018.
    16. Aurelio Patelli & Lorenzo Napolitano & Giulio Cimini & Andrea Gabrielli, 2021. "Geography of Science: Competitiveness and Inequality," Papers 2110.01615, arXiv.org.
    17. Liu, Jian-Guo & Li, Ren-De & Guo, Qiang & Zhang, Yi-Cheng, 2018. "Collective iteration behavior for online social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 490-497.
    18. 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.
    19. Zhang, Lin & Qi, Fan & Sivertsen, Gunnar & Liang, Liming & Campbell, David, 2023. "Gender differences in the patterns and consequences of changing specialization in scientific careers," SocArXiv ep5bx, Center for Open Science.
    20. Ruth Zárate Rueda & Yolima Ivonne Beltrán Villamizar & Luis Eduardo Becerra Ardila, 2023. "A Retrospective Approach to Pro-Environmental Behavior from Environmental Education: An Alternative from Sustainable Development," Sustainability, MDPI, vol. 15(6), pages 1-19, March.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0233997. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.