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Dynamic Evolution Research and System Implementation of International Soybean Trade Network Based on Complex Network

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Published:22 October 2018Publication History

ABSTRACT

As1 an important part of international grain trade, the trade volume of soybeans has continued to grow year by year, and its related research has received increasing attention from many scholars. This paper studies the global soybean trade data from 2000 to 2014, and built an international soybean trade network based on complex networks with the countries as the nodes and the inter-state trade relationships as the network links. Topological characteristics and their evolution, such as the average path length of the international soybean trade network, network clustering, network structure entropy, network reciprocity, etc. are mainly studied in this paper. The results show that in the international soybean trade, the trade relationship between countries is getting closer and closer. The heterogeneity of the network is not strong since some countries play important roles in the international soybean trade market while some countries have less participation. The international soybean trade network is a reciprocal network with the reciprocity between countries gradually increasing. This work explored the evolution of international soybean trade and provided a valuable reference for China to better participate in the international soybean trade market. At the same time, based on JAVA technology, the international soybean trade visualization tool and online service system have been developed as a practical feasibility solution for such applications.

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  1. Dynamic Evolution Research and System Implementation of International Soybean Trade Network Based on Complex Network

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      • Published in

        cover image ACM Other conferences
        CSAE '18: Proceedings of the 2nd International Conference on Computer Science and Application Engineering
        October 2018
        1083 pages
        ISBN:9781450365123
        DOI:10.1145/3207677

        Copyright © 2018 ACM

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        Publication History

        • Published: 22 October 2018

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        CSAE '18 Paper Acceptance Rate189of383submissions,49%Overall Acceptance Rate368of770submissions,48%

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