Statistical properties of the mutual transfer network among global football clubs

Li, Mingxia; Xiao, Qiao-Li; Wang, Yue; Zhou, Wei‐Xing

doi:10.1142/s0217979218503204

Cited by 6 publications

(11 citation statements)

References 46 publications

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“…The distributions for the insecticides (380891) networks in Figure 7A, the fungicides (380892) networks in Figure 7B, and the herbicides (380893) networks in Figure 7C exhibit a power-law scaling when the weights are not large, followed by a faster decay when the weights become larger. There is also a bimodal pattern for the fungicides (380892) networks in Figure 7B and the herbicides (380893) networks in Figure 7C, reminiscent of the bimodal distribution of some social networks [42][43][44]. The distributions for the disinfectants (380894) networks in Figure 7D and the rodenticides (380899) networks in Figure 7E do not show an evident power law.…”

Section: Weight Distributionmentioning

confidence: 87%

Structure and Evolution of the International Pesticide Trade Networks

Xie

Zhou

2021

Front. Phys.

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To meet the increasing demand for food around the world, pesticides are widely used and will continue to be widely used in agricultural production to reduce yield losses and maintain product quality. International pesticide trade serves to reallocate the distribution of pesticides around the world. We investigate the statistical properties of the international trade networks of five categories of pesticides from the view angle of temporal directed and weighted networks. We observed an overall increasing trend in network size, network density, average in- and out-degrees, average in- and out-strengths, temporal similarity, and link reciprocity, indicating that the rising globalization of pesticides trade is driving the networks denser. However, the distributions of link weights remain unchanged along time for the five categories of pesticides. In addition, all the networks are disassortatively mixed because large importers or exporters are more likely to trade with small exporters or importers. We also observed positive correlations between in-degree and out-degree, in-strength and out-strength, link reciprocity and in-degree, out-degree, in-strength, and out-strength, while node’s local clustering coefficient is negatively related to in-degree, out-degree, in-strength, and out-strength. We show that some structural and dynamic properties of the international pesticide trade networks are different from those of the international trade networks, highlighting the presence of idiosyncratic features of different goods and products in the international trade.

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Section: Weight Distributionmentioning

confidence: 87%

Structure and Evolution of the International Pesticide Trade Networks

Xie

Zhou

2021

Front. Phys.

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“…Complex networks have proven to be a very powerful approach to characterize and analyze a broad array of different complex systems [3][4][5][6][7], such as human migration [8][9][10], biological mathematics [11,12], technological [13][14][15][16][17] and finance systems [18][19][20][21][22][23][24]. These highly inter-coupled systems have been the focus of a great number of researches, which have investigated influential nodes of the systems.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Global Remittance Based on Complex Networks

Wen

et al. 2020

Front. Phys.

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Remittance, one money flow between immigrants and their relatives, is a major source of foreign exchange revenue for economies. Consisting of economies linked by the money flows, global remittance constitutes a network. In this paper, we use bilateral remittances of 210 economies for the time period 2010-2016 to construct a global remittance network (GRN) and then investigate the network's structural properties. We study the degree distribution of the network and find that it is of heterogeneity. Analyses of centrality measures reveal that some key economies, such as the United States, France, India and China, are always ranked the highest. We also detect 6 communities in the network, where economies in the same regional economy cooperative organizations tend to be classified in the same community. Intra-community flows account for 66.07% of total remittances, indicating that economies present the characteristic of regionalization. In addition, the results of the topological stability test show that GRN is fragile to node removal, particular the selective removal based on betweenness centrality.

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“…The fitted parameters are listed in table 1, in which we also present the results for the MFTN [26]. It shows that although the FTN and the MFTN have the same degree and strength distributions qualitatively, they have quantitative differences.…”

Section: Distributionsmentioning

confidence: 94%

“…In recent years, network analysis has been applied to study different networks constructed from variant attributes of the football market, such as the bipartite network of players and clubs [14], football passing networks among players [15][16][17][18][19], zone-specified passing networks [20][21][22][23], footballer transfer networks (FTNs) [24,25], and mutual footballer transfer networks (MFTNs) [26]. In this letter, we construct a direct transfer network to investigate the features of the transfer events of football players between different football club.…”

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confidence: 99%

Network analysis of the worldwide footballer transfer market

Li¹,

Zhou²,

Stanley³

2019

EPL

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The transfer of football players is an important part in football games. Most studies on the transfer of football players focus on the transfer system and transfer fees but not on the transfer behavior itself. Based on the 470,792 transfer records from 1990 to 2016 among 23,605 football clubs in 206 countries and regions, we construct a directed footballer transfer network (FTN), where the nodes are the football clubs and the links correspond to the footballer transfers. A systemic analysis is conduced on the topological properties of the FTN. We find that the in-degrees, out-degrees, in-strengths and out-strengths of nodes follow bimodal distributions (a power law with exponential decay), while the distribution of link weights has a power-law tail. We further figure out the correlations between node degrees, node strengths and link weights. We also investigate the general characteristics of different measures of network centrality. Our network analysis of the global footballer transfer market sheds new lights into the investigation of the characteristics of transfer activities.

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Statistical properties of the mutual transfer network among global football clubs

Cited by 6 publications

References 46 publications

Structure and Evolution of the International Pesticide Trade Networks

Structure and Evolution of the International Pesticide Trade Networks

Analysis of Global Remittance Based on Complex Networks

Network analysis of the worldwide footballer transfer market

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