Analysis on the Trade Networks of the Belt and Road Countries and Regions under Large Scale Shipping Data
SUN Tao;WU Lin;WANG Fei;WANG Qi;CHEN Zhao;XU Yongjun;Special Technology Research Center, Institute of Computing Technology, Chinese Academy of Sciences;
Among the 65 countries along the Belt and Road, 46 countries have registered ports of entry. At the same time, the trade by maritime shipping account for more than 75% of the total international trade. In order to fully understand the shipping trade in the countries and regions along the Belt and Road and assess the trade relations between countries and regions along the Belt and Road, we selected data which depicts the shipping history movements of the countries along the Belt and Road in the year of 2016 for study in this paper. Firstly,based on the method of rule determination, we excavated the Stop-port events of ships. By use of the ports in the countries of the Belt and Road as the main nodes, and the inter-port cargo transactions events as the edges, we have built the Belt and Road international shipping trade network. Based on this, the following network structure analyses of trade networks were conducted:(1) basic attributes analysis of the Belt and Road trade network,including network connectivity, degree distribution and average shortest path;(2) calculation of network node centrality, mainly using Eigenvector Centrality to evaluate the centrality of nodes in the trade network;(3) Using the concept of community mining in social network mining as the reference, and using the Fast Unfolding algorithm to discover the community of trading network. It can be seen that the trade between the countries and regions along the Belt and Road is intricately interwoven. By analyzing the degree distribution of nodes in the trade network, it can be clearly seen that there are small-world networks within the Belt and Road trade network.Further, Turkey, Russia and China are the three most influential counties in terms of the ports influence. By analyzing the results of the community detection, five major trade communities were identified. The distribution of these communities is basically in line with the geographical distribution. However, there are still some countries that are affected by special trade practices and their communities have broken regional restrictions. By building the trading network under large scale ship data, we evaluated the node's influence and analyzed the structure of the trade network more clearly on the basis of network analysis, and we hope this paper can help to better implement the Belt and Road Initiative strategy.
【CateGory Index】： F551
【CateGory Index】： F551