scholarly journals Multi-Attribute Community Detection in International Trade Network

2021 ◽  
Author(s):  
Rosanna Grassi ◽  
Paolo Bartesaghi ◽  
Stefano Benati ◽  
Gian Paolo Clemente
Keyword(s):  
International Trade ◽  
Community Detection ◽  
Optimal Solution ◽  
Centrality Measures ◽  
Trade Network ◽  
Trade Patterns ◽  
Economic Relationships ◽  
Clique Partitioning Problem ◽  
The Individual ◽  
International Trade Network

AbstractUnderstanding the structure of communities in a network has a great importance in the economic analysis. Communities are indeed characterized by specific properties, that are different from those of both the individual nodes and the whole network, and they can affect various processes on the network. In the International Trade Network, community detection aims to search sets of countries (or of trade sectors) which have a high intra-cluster connectivity and a low inter-cluster connectivity. In general, exchanges among countries occur according to preferential economic relationships ranging over different sectors. In this paper, we combine community detection with specific topological indicators, such as centrality measures. As a result, a new weighted network is constructed from the original one, in which weights are determined taking into account all the topological indicators in a multi-criteria approach. To solve the resulting Clique Partitioning Problem and find homogeneous group of nations, we use a new fast algorithm, based on quick descents to a local optimal solution. The analysis allows to cluster countries by interconnections, economic power and intensity of trade, giving an important overview on the international trade patterns.

Distance-varying assortativity and clustering of the international trade network

2018 ◽  
Vol 6 (4) ◽  
pp. 517-544
Author(s):  
ANGELA ABBATE ◽  
LUCA DE BENEDICTIS ◽  
GIORGIO FAGIOLO ◽  
LUCIA TAJOLI
Keyword(s):  
International Trade ◽  
Trade Network ◽  
Trade Patterns ◽  
Linear Evolution ◽  
Non Linear ◽  
Trading Partners ◽  
Similar Distance ◽  
Triangular Trade ◽  
Geographical Space ◽  
International Trade Network

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.

Heterogeneous Influence Maximization Through Community Detection in Social Networks

2021 ◽  
Vol 12 (4) ◽  
pp. 118-131
Author(s):  
Jaya Krishna Raguru ◽  
Devi Prasad Sharma
Keyword(s):  
Community Detection ◽  
Greedy Algorithms ◽  
Computational Cost ◽  
Optimal Solution ◽  
Influence Maximization ◽  
Centrality Measures ◽  
Influence Spread ◽  
Real World Datasets ◽  
Initial Seed ◽  
High Computational Cost

The problem of identifying a seed set composed of K nodes that increase influence spread over a social network is known as influence maximization (IM). Past works showed this problem to be NP-hard and an optimal solution to this problem using greedy algorithms achieved only 63% of spread. However, this approach is expensive and suffered from performance issues like high computational cost. Furthermore, in a network with communities, IM spread is not always certain. In this paper, heterogeneous influence maximization through community detection (HIMCD) algorithm is proposed. This approach addresses initial seed nodes selection in communities using various centrality measures, and these seed nodes act as sources for influence spread. A parallel influence maximization is applied with the aid of seed node set contained in each group. In this approach, graph is partitioned and IM computations are done in a distributed manner. Extensive experiments with two real-world datasets reveals that HCDIM achieves substantial performance improvement over state-of-the-art techniques.

China's Geostrategic Approach to Trade in Pursuit of Global Centrality

2021 ◽  
pp. 148-175
Author(s):  
Guy-Maurille Massamba
Keyword(s):  
International Trade ◽  
National Character ◽  
Global Trade ◽  
Trade Expansion ◽  
Trade Network ◽  
Central Node ◽  
Global Power ◽  
Trade Partners ◽  
International Trade Network

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.

COMPLEX NETWORKS AND MINIMAL SPANNING TREES IN INTERNATIONAL TRADE NETWORK

2012 ◽  
Vol 16 ◽  
pp. 51-60 ◽  
Author(s):  
SEONG EUN MAENG ◽  
HYUNG WOOC CHOI ◽  
JAE WOO LEE
Keyword(s):  
International Trade ◽  
Power Law ◽  
Betweenness Centrality ◽  
World Trade ◽  
Spanning Trees ◽  
Distribution Functions ◽  
Cumulative Probability ◽  
Trade Network ◽  
Data Set ◽  
International Trade Network

The wealth of a nation is changed by the internal economic growth of a nation and by the international trade among countries. Trade between countries are one of their most important interactions and thus expects to affect crucially the wealth distribution over countries. We reviewed the network properties of the international trade networks (ITN). We analyzed data sets of world trade. The data set include a total number of 190 countries from 1950 to 2000. We observed that the world trade network showed the uneven trading relationships which are measured by the disparity. The effective disparity followed a power law, < D(k) >~ tδ, for the import and export network. We also construct the minimal spanning tree(MST) of international trade network, where each node is a country and directed links connecting them represent money flow from a source node to a target one. The topology of the MST shows the flow patterns of the international trades. From the MST we can identify the sub-economic zone if we delete the hub node. We observed that the cumulative degree distribution functions follow the power law, P>(k) ~ k-α, with the average exponent α = 1.1(1)). We also calculated the betweenness centrality(BC) of the MST. The cumulative probability distribution of the betweenness centrality follows the power law, P>( BC ) ~ BC -β, with the average exponent β = 1.09(7).

Understanding international trade network complexity of platinum: The case of Japan

2016 ◽  
Vol 49 ◽  
pp. 415-421 ◽  
Author(s):  
Shohei Tokito ◽  
Shigemi Kagawa ◽  
Keisuke Nansai
Keyword(s):  
International Trade ◽  
Trade Network ◽  
International Trade Network

Anahilapura: Understanding Its Expansive Network during the Time of the Chaulukyas

2018 ◽  
Vol 6 (2) ◽  
pp. 236-245
Author(s):  
Suchandra Ghosh
Keyword(s):  
International Trade ◽  
Indian Ocean ◽  
Red Sea ◽  
Persian Gulf ◽  
Trade Network ◽  
Trading Zone ◽  
The Indian Ocean ◽  
The Persian Gulf ◽  
Sea Area ◽  
International Trade Network

Abstract Gujarat’s role in the international trade network has long been researched. During the first half of the second millennium CE, the Indian Ocean emerged as a vast trading zone; its western termini were Siraf/Basra/Baghdad in the Persian Gulf zone and Alexandria/Fustat (old Cairo) in the Red Sea area, while the eastern terminus extended up to the ports in China. However, this essay privileges a single place, Anahilapura, which acted as a hinterland to many of the ports of Gujarat.

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