IDEAS home Printed from https://ideas.repec.org/a/bla/jinfst/v67y2016i9p2223-2245.html
   My bibliography  Save this article

Disciplinary knowledge production and diffusion in science

Author

Listed:
  • Erjia Yan

Abstract

No abstract is available for this item.

Suggested Citation

  • Erjia Yan, 2016. "Disciplinary knowledge production and diffusion in science," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(9), pages 2223-2245, September.
  • Handle: RePEc:bla:jinfst:v:67:y:2016:i:9:p:2223-2245
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1002/asi.23541
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    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. Yue, Zenghui & Xu, Haiyun & Yuan, Guoting & Pang, Hongshen, 2019. "Modeling study of knowledge diffusion in scientific collaboration networks based on differential dynamics: A case study in graphene field," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 375-391.
    2. Pan, Xuelian & Yan, Erjia & Cui, Ming & Hua, Weina, 2018. "Examining the usage, citation, and diffusion patterns of bibliometric mapping software: A comparative study of three tools," Journal of Informetrics, Elsevier, vol. 12(2), pages 481-493.
    3. Saeed-Ul Hassan & Iqra Safder & Anam Akram & Faisal Kamiran, 2018. "A novel machine-learning approach to measuring scientific knowledge flows using citation context analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(2), pages 973-996, August.
    4. Kai Nishikawa, 2023. "How and why are citations between disciplines made? A citation context analysis focusing on natural sciences and social sciences and humanities," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(5), pages 2975-2997, May.
    5. Yujie Zhang & Hongzhen Li & Jingyi Mao & Guoxiu He & Yunhan Yang & Zhuoren Jiang & Yufeng Duan, 2023. "COVID-19: a disruptive impact on the knowledge support of references," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(8), pages 4791-4823, August.
    6. Dejing Kong & Jianzhong Yang & Lingfeng Li, 2020. "Early identification of technological convergence in numerical control machine tool: a deep learning approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 1983-2009, December.
    7. Wu, Chaojiang & Yan, Erjia & Hill, Chelsey, 2017. "Disciplinary knowledge diffusion in business research," Journal of Informetrics, Elsevier, vol. 11(2), pages 655-668.
    8. Yu-Wei Chang, 2018. "Examining interdisciplinarity of library and information science (LIS) based on LIS articles contributed by non-LIS authors," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(3), pages 1589-1613, September.
    9. Sergey Kolesnikov & Eriko Fukumoto & Barry Bozeman, 2018. "Researchers’ risk-smoothing publication strategies: Is productivity the enemy of impact?," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(3), pages 1995-2017, September.
    10. Wang, Shiyun & Mao, Jin & Lu, Kun & Cao, Yujie & Li, Gang, 2021. "Understanding interdisciplinary knowledge integration through citance analysis: A case study on eHealth," Journal of Informetrics, Elsevier, vol. 15(4).
    11. Mao, Jin & Liang, Zhentao & Cao, Yujie & Li, Gang, 2020. "Quantifying cross-disciplinary knowledge flow from the perspective of content: Introducing an approach based on knowledge memes," Journal of Informetrics, Elsevier, vol. 14(4).

    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:jinfst:v:67:y:2016:i:9:p:2223-2245. 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.