An International Trade Network Analysis of the Environment

2009 ◽  
Vol 16 (3) ◽  
pp. 271-284 ◽  
Author(s):  
Daniel E. May
2014 ◽  
Vol 513-517 ◽  
pp. 2059-2062
Author(s):  
Lei Ming Yan ◽  
Jin Han

Community discovery is a crucial task in social network analysis, especially in describing the evolution of social networks. Although some works have focused on finding the dynamic community, there are still some open problems need to be conquered, such as analyzing the dynamic and weighted community. In this paper, we propose a framework for analyzing weighted communities and their evolutions via clustering correlated weight vectors to enhance existing community detection algorithms. The International trade network is used to verify our framework. Experiments show that the framework discovers and captures the evolving behaviors with temporal elements and weight values.


Author(s):  
Guy-Maurille Massamba

The geostrategic approach refers to China's method to rise as global power through worldwide trade expansion and the development of its military and naval capabilities. It creates clusters of countries interlinked as China's trade partners, thus being assets to its global ascent. China's importance in global trade is a function of its partners' behavior embracing its trade mechanism. The edges connecting nodes are multidirectional, implying that countries are as much interested in their China-induced interlinkages as they are in their partnership with China. This results in China's centrality, a quality gained from being dominant in trade partnerships in terms of numbers and significance. This chapter examines the approach, process, and historical, geographic, and behavioral components that China uses in its ascent as central node in the international trade network. It explores how underlying dimensions making China's national character conjointly devise its behavior in global trade.


2018 ◽  
Vol 6 (4) ◽  
pp. 517-544
Author(s):  
ANGELA ABBATE ◽  
LUCA DE BENEDICTIS ◽  
GIORGIO FAGIOLO ◽  
LUCIA TAJOLI

AbstractIn this paper, we study how the topology of the International Trade Network (ITN) changes in geographical space, and along time. We employ geographical distance between countries in the world to filter the links in the ITN, building a sequence of subnetworks, each one featuring trade links occurring at similar distance. We then test if the assortativity and clustering of ITN subnetworks changes as distance increases, and we find that this is indeed the case: distance strongly impacts, in a non-linear way, the topology of the ITN. We show that the ITN is disassortative at long distances, while it is assortative at short ones. Similarly, the main determinant of the overall high-ITN clustering level are triangular trade triples between geographically close countries. This means that trade partnership choices and trade patterns are highly differentiated over different distance ranges, even after controlling for the economic size and income per capita of trading partners, and it is persistent over time. This evidence has relevant implications for the non-linear evolution of globalization.


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