IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v63y2005i2d10.1007_s11192-005-0212-4.html
   My bibliography  Save this article

Analysis of the field of physical chemistry of surfactants with the Unified Scienctometric Model. Fit of relational and activity indicators

Author

Listed:
  • R. Bailón-Moreno

    (Departamento de Ingeniería Química. Facultad de Ciencias, Campus de Fuentenueva Universidad de Granada)

  • E. Jurado-Alameda

    (Departamento de Ingeniería Química. Facultad de Ciencias, Campus de Fuentenueva Universidad de Granada)

  • R. Ruiz-Baños

    (Departamento de Biblioteconomía y Documentación, Facultad de Biblioteconomía y Documentación, Universidad de Granada)

  • J. P. Courtial

    (Laboratoire de Psychologie - Education - Cognition Développement (LabECD), Université de Nantes)

Abstract

Summary By the information system of CoPalRed© and with the treatment of 63,543 bibliographical references of scientific articles, the field of surfactants has been analysed in the light of the Unified Scientometric Model. It was found that the distributions of actors (countries, centres, and research laboratories, journals, researchers, key words of documents) fit Zif's Unified Law better than the Zipf-Mandelbrot Law. The model showed an especially good fit for relational indicators such as density and centrality. Using the Unified Bradford Law, the three zones fit were: core, straight fraction, and Groos droop. The fractality index was used to verify that Science can present fractal as well as transfractal structures. In conclusion, the Unified Scientometric Model is, for its flexibility and its integrating capacity, an appropriate model for representing Science, joining non-relational with relational Scientometrics under the same paradigm.

Suggested Citation

  • R. Bailón-Moreno & E. Jurado-Alameda & R. Ruiz-Baños & J. P. Courtial, 2005. "Analysis of the field of physical chemistry of surfactants with the Unified Scienctometric Model. Fit of relational and activity indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 63(2), pages 259-276, April.
  • Handle: RePEc:spr:scient:v:63:y:2005:i:2:d:10.1007_s11192-005-0212-4
    DOI: 10.1007/s11192-005-0212-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-005-0212-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11192-005-0212-4?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. Robert Tomaszewski, 2017. "Citations to chemical resources in scholarly articles: CRC Handbook of Chemistry and Physics and The Merck Index," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(3), pages 1865-1879, September.
    2. Gaofeng Wang & Shuai Li & Zihao Zhang & Yanning Hou & Changhoon Shin, 2023. "A Visual Knowledge Map Analysis of Cross-Border Agri-Food Supply Chain Research Based on CiteSpace," Sustainability, MDPI, vol. 15(14), pages 1-28, July.
    3. Tianlong Yu & Hao Yang & Xiaowei Luo & Yifeng Jiang & Xiang Wu & Jingqi Gao, 2021. "Scientometric Analysis of Disaster Risk Perception: 2000–2020," IJERPH, MDPI, vol. 18(24), pages 1-19, December.
    4. Feng Hu & Wei Liu & Sang-Bing Tsai & Junbin Gao & Ning Bin & Quan Chen, 2018. "An Empirical Study on Visualizing the Intellectual Structure and Hotspots of Big Data Research from a Sustainable Perspective," Sustainability, MDPI, vol. 10(3), pages 1-19, March.
    5. Judith Nyulas & Ștefan Dezsi & Adrian Niță & Raluca-Andreea Toma & Ana-Maria Lazăr, 2024. "Trends and Future Directions in Analysing Attractiveness of Geoparks Using an Automated Merging Method of Multiple Databases—R-Based Bibliometric Analysis," Land, MDPI, vol. 13(10), pages 1-30, October.
    6. Cobo, M.J. & López-Herrera, A.G. & Herrera-Viedma, E. & Herrera, F., 2011. "An approach for detecting, quantifying, and visualizing the evolution of a research field: A practical application to the Fuzzy Sets Theory field," Journal of Informetrics, Elsevier, vol. 5(1), pages 146-166.

    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:spr:scient:v:63:y:2005:i:2:d:10.1007_s11192-005-0212-4. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.