IDEAS home Printed from https://ideas.repec.org/a/bla/jamist/v64y2013i2p265-279.html
   My bibliography  Save this article

Venue‐author‐coupling: A measure for identifying disciplines through author communities

Author

Listed:
  • Chaoqun Ni
  • Cassidy R. Sugimoto
  • Jiepu Jiang

Abstract

Conceptualizations of disciplinarity often focus on the social aspects of disciplines; that is, disciplines are defined by the set of individuals who participate in their activities and communications. However, operationalizations of disciplinarity often demarcate the boundaries of disciplines by standard classification schemes, which may be inflexible to changes in the participation profile of that discipline. To address this limitation, a metric called venue‐author‐coupling (VAC) is proposed and illustrated using journals from the Journal Citation Report's (JCR) library science and information science category. As JCRs are some of the most frequently used categories in bibliometric analyses, this allows for an examination of the extent to which the journals in JCR categories can be considered as proxies for disciplines. By extending the idea of bibliographic coupling, VAC identifies similarities among journals based on the similarities of their author profiles. The employment of this method using information science and library science journals provides evidence of four distinct subfields, that is, management information systems, specialized information and library science, library science‐focused, and information science‐focused research. The proposed VAC method provides a novel way to examine disciplinarity from the perspective of author communities.

Suggested Citation

  • Chaoqun Ni & Cassidy R. Sugimoto & Jiepu Jiang, 2013. "Venue‐author‐coupling: A measure for identifying disciplines through author communities," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 64(2), pages 265-279, February.
    • Handle: RePEc:bla:jamist:v:64:y:2013:i:2:p:265-279
    DOI: 10.1002/asi.22630
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/asi.22630
    Download Restriction: no
    File URL: https://libkey.io/10.1002/asi.22630?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
    ---><---

    Citations

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


    Cited by:

    1. Xie, Yundong & Wu, Qiang & Zhang, Peng & Li, Xingchen, 2020. "Information Science and Library Science (IS-LS) journal subject categorisation and comparison based on editorship information," Journal of Informetrics, Elsevier, vol. 14(4).
    2. Erjia Yan, 2014. "Topic-based Pagerank: toward a topic-level scientific evaluation," Scientometrics, Springer;Akadémiai Kiadó, vol. 100(2), pages 407-437, August.
    3. Yongjun Zhu & Erjia Yan, 2015. "Dynamic subfield analysis of disciplines: an examination of the trading impact and knowledge diffusion patterns of computer science," Scientometrics, Springer;Akadémiai Kiadó, vol. 104(1), pages 335-359, July.
    4. Chiara Carusi & Giuseppe Bianchi, 2020. "A look at interdisciplinarity using bipartite scholar/journal networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(2), pages 867-894, February.
    5. Mu-hsuan Huang & Wang-Ching Shaw & Chi-Shiou Lin, 2019. "One category, two communities: subfield differences in “Information Science and Library Science” in Journal Citation Reports," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(2), pages 1059-1079, May.
    6. Jeppe Nicolaisen & Tove Faber Frandsen, 2022. "Epistemic community formation: a bibliometric study of recurring authors in medical journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(7), pages 4167-4189, July.
    7. Baccini, Federica & Barabesi, Lucio & Baccini, Alberto & Khelfaoui, Mahdi & Gingras, Yves, 2022. "Similarity network fusion for scholarly journals," Journal of Informetrics, Elsevier, vol. 16(1).
    8. Jing Zhang & Xiaomin Liu & Lili Wu, 2016. "The study of subject-classification based on journal coupling and expert subject-classification system," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(3), pages 1149-1170, June.

    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:bla:jamist:v:64:y:2013:i:2:p:265-279. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.asis.org .

    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.