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

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  • 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
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    Cited by:

    1. Urdiales, Cristina & Guzmán, Eduardo, 2024. "An automatic and association-based procedure for hierarchical publication subject categorization," Journal of Informetrics, Elsevier, vol. 18(1).
    2. 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).
    3. Erjia Yan, 2014. "Topic-based Pagerank: toward a topic-level scientific evaluation," Scientometrics, Springer;Akadémiai Kiadó, vol. 100(2), pages 407-437, August.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. Baccini, Federica & Barabesi, Lucio & Baccini, Alberto & Khelfaoui, Mahdi & Gingras, Yves, 2022. "Similarity network fusion for scholarly journals," Journal of Informetrics, Elsevier, vol. 16(1).
    9. 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.

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