IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v441y2016icp81-84.html
   My bibliography  Save this article

Density: A measure of the diversity of concepts addressed in semantic networks

Author

Listed:
  • Pereira, H.B.B.
  • Fadigas, I.S.
  • Monteiro, R.L.S.
  • Cordeiro, A.J.A.
  • Moret, M.A.

Abstract

In this paper, we studied density effects in semantic networks constructed from a database of titles of papers published in scientific journals as a parameter to indicate the diversity of concepts in a journal. The proposed method essentially consists of fixing the number of titles for all of the studied scientific journals and analyzing the behavior of the density variation curves with regard to the inclusion of cliques (that is, complete networks associated with the titles). We observed that density behaves as a critically self-organized object when titles (cliques) are included in the network.

Suggested Citation

  • Pereira, H.B.B. & Fadigas, I.S. & Monteiro, R.L.S. & Cordeiro, A.J.A. & Moret, M.A., 2016. "Density: A measure of the diversity of concepts addressed in semantic networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 441(C), pages 81-84.
    • Handle: RePEc:eee:phsmap:v:441:y:2016:i:c:p:81-84
    DOI: 10.1016/j.physa.2015.08.024
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437115006792
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2015.08.024?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. Davi Alves Oliveira & Hernane Borges de Barros Pereira, 2024. "Modeling texts with networks: comparing five approaches to sentence representation," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 97(6), pages 1-12, June.
    2. Inácio Sousa Fadigas & Marcos Grilo & Hernane Borges Barros Pereira, 2023. "Scientific journal disciplinarity quantification and sorting using a network index," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(3), pages 2563-2573, June.

    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:eee:phsmap:v:441:y:2016:i:c:p:81-84. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.