IDEAS home Printed from
   My bibliography  Save this article

Exploring the topic hierarchy of digital library research in China using keyword networks: a K-core decomposition approach


  • Lu Xiao

    (Nanjing University)

  • Guo Chen

    () (Nanjing University of Science and Technology)

  • Jianjun Sun

    (Nanjing University)

  • Shuguang Han

    (University of Pittsburgh)

  • Chengzhi Zhang

    (Nanjing University of Science and Technology)


Exploring the topic hierarchy of a research field can help us better recognize its intellectual structure. This paper proposes a new method to automatically discover the topic hierarchy, in which the keyword network is constructed to represent topics and their relations, and then decomposed hierarchically into shells using the K-core decomposition method. Adjacent shells with similar morphology are merged into layers according to their density and clustering coefficient. In the keyword network of the digital library field in China, we discover four different layers. The basic layer contains 17 tightly-interconnected core concepts which form the knowledge base of the field. The middle layer contains 13 mediator concepts which are directly connected to technology concepts in the basic layer, showing the knowledge evolution of the field. The detail layer contains 65 concrete concepts which can be grouped into 13 clusters, indicating the research specializations of the field. The marginal layer contains peripheral or isolated concepts.

Suggested Citation

  • Lu Xiao & Guo Chen & Jianjun Sun & Shuguang Han & Chengzhi Zhang, 2016. "Exploring the topic hierarchy of digital library research in China using keyword networks: a K-core decomposition approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(3), pages 1085-1101, September.
  • Handle: RePEc:spr:scient:v:108:y:2016:i:3:d:10.1007_s11192-016-2051-x
    DOI: 10.1007/s11192-016-2051-x

    Download full text from publisher

    File URL:
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

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

    References listed on IDEAS

    1. Chen, Guo & Xiao, Lu, 2016. "Selecting publication keywords for domain analysis in bibliometrics: A comparison of three methods," Journal of Informetrics, Elsevier, vol. 10(1), pages 212-223.
    2. Verspagen, Bart & Werker, Claudia, 2004. "Keith Pavitt and the Invisible College of the Economics of Technology and Innovation," Research Policy, Elsevier, vol. 33(9), pages 1419-1431, November.
    3. Son Hoang Nguyen & Gobinda Chowdhury, 2013. "Interpreting the knowledge map of digital library research (1990–2010)," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 64(6), pages 1235-1258, June.
    4. Star X. Zhao & Paul L. Zhang & Jiang Li & Alice M. Tan & Fred Y. Ye, 2014. "Abstracting the core subnet of weighted networks based on link strengths," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(5), pages 984-994, May.
    Full references (including those not matched with items on IDEAS)


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

    Cited by:

    1. Zhichao Ba & Yujie Cao & Jin Mao & Gang Li, 2019. "A hierarchical approach to analyzing knowledge integration between two fields—a case study on medical informatics and computer science," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(3), pages 1455-1486, June.


    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:108:y:2016:i:3:d:10.1007_s11192-016-2051-x. See general information about how to correct material in RePEc.

    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). General contact details of provider: .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.