IDEAS home Printed from https://ideas.repec.org/a/igg/jaeis0/v11y2020i3p61-74.html
   My bibliography  Save this article

Provincial Linkage Characteristics of Hog Price in China Based on Linkage Social Network Analysis Method

Author

Listed:
  • Jiyun Bai

    (Northeast Agricultural University, Harbin, China)

  • Muyan Liu

    (College of Engineering, Northeast Agricultural University, Harbin, China)

  • Li Ma

    (College of Engineering, Northeast Agricultural University, Harbin, China)

  • Jun Meng

    (College of Arts and Sciences, Northeast Agricultural University, Harbin, China)

Abstract

In order to obtain the visual data of linkage structure and network characteristics of hog price among provinces in China, an improved analysis method of social network correlation was proposed in this article. The lift of association rules were introduced to analyze the correlation of hog prices in different provinces in China and taken as the weight matrix of network analysis. Besides, based on social network analysis parameters and UCINET visualization technology, network analysis was carried out on the linkage relation and linkage characteristics. The application results show that, the lift of association rules can quantitatively and precisely obtain the correlation and differences of tendency of hog price, and the established network structure and parameters can visually and quantitatively present the linkage characteristics of hog price among regions and provinces.

Suggested Citation

  • Jiyun Bai & Muyan Liu & Li Ma & Jun Meng, 2020. "Provincial Linkage Characteristics of Hog Price in China Based on Linkage Social Network Analysis Method," International Journal of Agricultural and Environmental Information Systems (IJAEIS), IGI Global, vol. 11(3), pages 61-74, July.
    • Handle: RePEc:igg:jaeis0:v:11:y:2020:i:3:p:61-74
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJAEIS.2020070105
    Download Restriction: no
    ---><---

    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:igg:jaeis0:v:11:y:2020:i:3:p:61-74. 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

    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.