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International trade negotiation analysis: network and semantic knowledge infrastructure

Author

Listed:
  • Jacob Wood

    (Korea University of Technology and Education)

  • Gohar Feroz Khan

    (Korea University of Technology and Education)

Abstract

This study utilizes the social network analysis technique to analyze and better understand the semantic and knowledge networks that are associated with the field of international trade and more specifically international free trade agreements. This study builds on the research that currently exists in the field of international trade negotiation by using the SNA technique to construct, visualize, and investigate the International Trade networked knowledge infrastructure by analyzing 3074 publications, 1054 journal sources, 4047 authors, 1516 organizations, 87 countries and keywords associated with this field of research. The network and ego level properties—such as, degree centralities, density, components, structural holes, and degree distribution—suggest that the international trade co-authorship network analyzed is relatively fragmented. The knowledge and sematic networks exhibit power law distribution in which the incoming nodes and links prefer to attach to the nodes that are already well connected. The study also sheds light on the emerging and fading themes in the domain.

Suggested Citation

  • Jacob Wood & Gohar Feroz Khan, 2015. "International trade negotiation analysis: network and semantic knowledge infrastructure," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(1), pages 537-556, October.
    • Handle: RePEc:spr:scient:v:105:y:2015:i:1:d:10.1007_s11192-015-1651-1
    DOI: 10.1007/s11192-015-1651-1
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    Cited by:

    1. S. Lozano & L. Calzada-Infante & B. Adenso-Díaz & S. García, 2019. "Complex network analysis of keywords co-occurrence in the recent efficiency analysis literature," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(2), pages 609-629, August.
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    3. Xiao Zhou & Lu Huang & Yi Zhang & Miaomiao Yu, 2019. "A hybrid approach to detecting technological recombination based on text mining and patent network analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(2), pages 699-737, November.
    4. Woocheol Kim & Gohar Feroz Khan & Jacob Wood & Muhammad Tariq Mahmood, 2016. "Employee Engagement for Sustainable Organizations: Keyword Analysis Using Social Network Analysis and Burst Detection Approach," Sustainability, MDPI, vol. 8(7), pages 1-11, July.

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