IDEAS home Printed from https://ideas.repec.org/h/wsi/wschap/9789813234482_0005.html
   My bibliography  Save this book chapter

Data Analytics Applied in CNKI Databases Search Log: Understanding Chinese Content Users in North America

In: Knowledge Discovery and Data Design Innovation Proceedings of the International Conference on Knowledge Management (ICKM 2017)

Author

Listed:
  • Xin Wang
  • Hsia-Ching Chang
  • Jiangping Chen
  • Jie Yang

Abstract

Chinese immigrants are the third largest foreign-born minority group in U.S. Also, there is a rapid growing trend of educational exchange between U.S. and China. However, few studies have been carried out to examine North America users’ interests and information behavior in terms of using Chinese content. This study collected and analyzed approximately one million transaction log data records to identify the most frequently used content types and the most popular reading topics from 2014 to 2016. The preliminary analysis indicated that Chinese content users in North America were not only interested in accessing textual information but also visual information. In terms of the most popular topics, Chinese content readers mainly focus on topics related to social science and humanities, but their reading interests were also expanded to technology-related topics in recent years.

Suggested Citation

  • Xin Wang & Hsia-Ching Chang & Jiangping Chen & Jie Yang, 2017. "Data Analytics Applied in CNKI Databases Search Log: Understanding Chinese Content Users in North America," World Scientific Book Chapters, in: Daniel Gelaw Alemneh & Jeff Allen & Suliman Hawamdeh (ed.), Knowledge Discovery and Data Design Innovation Proceedings of the International Conference on Knowledge Management (ICKM 2017), chapter 5, pages 89-105, World Scientific Publishing Co. Pte. Ltd..
  • Handle: RePEc:wsi:wschap:9789813234482_0005
    as

    Download full text from publisher

    File URL: https://www.worldscientific.com/doi/pdf/10.1142/9789813234482_0005
    Download Restriction: Ebook Access is available upon purchase.

    File URL: https://www.worldscientific.com/doi/abs/10.1142/9789813234482_0005
    Download Restriction: Ebook Access is available upon purchase.
    ---><---

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

    More about this item

    Keywords

    Knowledge Discovery; Big Data; Data Science; Data Analytics; Innovation;
    All these keywords.

    JEL classification:

    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General

    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:wsi:wschap:9789813234482_0005. 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscientific.com/page/worldscibooks .

    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.