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A geovisual analytic approach to understanding geo-social relationships in the international trade network.

Luo W, Yin P, Di Q, Hardisty F, MacEachren AM - PLoS ONE (2014)

Bottom Line: This research aims to address this challenge through the framework of geovisual analytics.In addition to demonstrating the potential of visual analytics to provide insight concerning complex geo-social relationships at a global scale, the research also addresses the challenge of validating insights derived through interactive geovisual analytics.We develop two indicators to quantify the observed patterns, and then use a Monte-Carlo approach to support the hypothesis developed above.

View Article: PubMed Central - PubMed

Affiliation: GeoVISTA Center, Department of Geography, Pennsylvania State University, University Park, Pennsylvania, United States of America.

ABSTRACT
The world has become a complex set of geo-social systems interconnected by networks, including transportation networks, telecommunications, and the internet. Understanding the interactions between spatial and social relationships within such geo-social systems is a challenge. This research aims to address this challenge through the framework of geovisual analytics. We present the GeoSocialApp which implements traditional network analysis methods in the context of explicitly spatial and social representations. We then apply it to an exploration of international trade networks in terms of the complex interactions between spatial and social relationships. This exploration using the GeoSocialApp helps us develop a two-part hypothesis: international trade network clusters with structural equivalence are strongly 'balkanized' (fragmented) according to the geography of trading partners, and the geographical distance weighted by population within each network cluster has a positive relationship with the development level of countries. In addition to demonstrating the potential of visual analytics to provide insight concerning complex geo-social relationships at a global scale, the research also addresses the challenge of validating insights derived through interactive geovisual analytics. We develop two indicators to quantify the observed patterns, and then use a Monte-Carlo approach to support the hypothesis developed above.

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Related in: MedlinePlus

The third run of the CONCOR process continues to subdivide groups.Figure 4A 4B, and 4C belong to the economically core countries, whereas Figure 4D, 4E, 4F, and 4G belong to the economic periphery countries.
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pone-0088666-g004: The third run of the CONCOR process continues to subdivide groups.Figure 4A 4B, and 4C belong to the economically core countries, whereas Figure 4D, 4E, 4F, and 4G belong to the economic periphery countries.

Mentions: The third run of CONCOR applied to the ITN again subdivides the previously identified groups into seven different subgroups (Figure 4) (A list of countries for each group is in File S1.). At this level the geographies are considerably more complex but this research highlights three features. First, only seven new subgroups are identified in this level: CONCOR does not divide countries depicted in Figure 3A any further, resulting in the same group of countries in Figure 4A, because economically core countries in this group have highly similar import and export trade partners. Second, some groups of countries at this level further confirm a core-periphery hierarchical structure in terms of the ITN: the top economically core countries in Figure 4A; a clear distinction between east African countries (the second least developing places) in Figure 4F and west African countries (the least developing regions) in Figure 4G. Third, the role that spatial and social relationships play in terms of the ITN identified by the third level of CONCOR becomes more noticeable. Core countries in Figure 4A, Figure 4B, and Figure 4C have their own distinct geographical regions (i.e., North America, Europe), but social relationships to connect different regions are also strong. Figure 4D and Figure 4E identify two distinct geographical regions (Central America and Central Asia) compared to Figure 3C that put both into the same social group. The distinct geographical regions suggest that spatial constraints are stronger than social connections between the two regions at this network level. Comparing the two distinct geographical regions identified in Figure 4D and Figure 4E to distinct geographical regions (i.e., North America, Europe, and Austria) in Figure 4A suggests that spatial constraints have less impact on economically core countries and more impact on economic periphery countries to determine the international trade partners they have.


A geovisual analytic approach to understanding geo-social relationships in the international trade network.

Luo W, Yin P, Di Q, Hardisty F, MacEachren AM - PLoS ONE (2014)

The third run of the CONCOR process continues to subdivide groups.Figure 4A 4B, and 4C belong to the economically core countries, whereas Figure 4D, 4E, 4F, and 4G belong to the economic periphery countries.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3928244&req=5

pone-0088666-g004: The third run of the CONCOR process continues to subdivide groups.Figure 4A 4B, and 4C belong to the economically core countries, whereas Figure 4D, 4E, 4F, and 4G belong to the economic periphery countries.
Mentions: The third run of CONCOR applied to the ITN again subdivides the previously identified groups into seven different subgroups (Figure 4) (A list of countries for each group is in File S1.). At this level the geographies are considerably more complex but this research highlights three features. First, only seven new subgroups are identified in this level: CONCOR does not divide countries depicted in Figure 3A any further, resulting in the same group of countries in Figure 4A, because economically core countries in this group have highly similar import and export trade partners. Second, some groups of countries at this level further confirm a core-periphery hierarchical structure in terms of the ITN: the top economically core countries in Figure 4A; a clear distinction between east African countries (the second least developing places) in Figure 4F and west African countries (the least developing regions) in Figure 4G. Third, the role that spatial and social relationships play in terms of the ITN identified by the third level of CONCOR becomes more noticeable. Core countries in Figure 4A, Figure 4B, and Figure 4C have their own distinct geographical regions (i.e., North America, Europe), but social relationships to connect different regions are also strong. Figure 4D and Figure 4E identify two distinct geographical regions (Central America and Central Asia) compared to Figure 3C that put both into the same social group. The distinct geographical regions suggest that spatial constraints are stronger than social connections between the two regions at this network level. Comparing the two distinct geographical regions identified in Figure 4D and Figure 4E to distinct geographical regions (i.e., North America, Europe, and Austria) in Figure 4A suggests that spatial constraints have less impact on economically core countries and more impact on economic periphery countries to determine the international trade partners they have.

Bottom Line: This research aims to address this challenge through the framework of geovisual analytics.In addition to demonstrating the potential of visual analytics to provide insight concerning complex geo-social relationships at a global scale, the research also addresses the challenge of validating insights derived through interactive geovisual analytics.We develop two indicators to quantify the observed patterns, and then use a Monte-Carlo approach to support the hypothesis developed above.

View Article: PubMed Central - PubMed

Affiliation: GeoVISTA Center, Department of Geography, Pennsylvania State University, University Park, Pennsylvania, United States of America.

ABSTRACT
The world has become a complex set of geo-social systems interconnected by networks, including transportation networks, telecommunications, and the internet. Understanding the interactions between spatial and social relationships within such geo-social systems is a challenge. This research aims to address this challenge through the framework of geovisual analytics. We present the GeoSocialApp which implements traditional network analysis methods in the context of explicitly spatial and social representations. We then apply it to an exploration of international trade networks in terms of the complex interactions between spatial and social relationships. This exploration using the GeoSocialApp helps us develop a two-part hypothesis: international trade network clusters with structural equivalence are strongly 'balkanized' (fragmented) according to the geography of trading partners, and the geographical distance weighted by population within each network cluster has a positive relationship with the development level of countries. In addition to demonstrating the potential of visual analytics to provide insight concerning complex geo-social relationships at a global scale, the research also addresses the challenge of validating insights derived through interactive geovisual analytics. We develop two indicators to quantify the observed patterns, and then use a Monte-Carlo approach to support the hypothesis developed above.

Show MeSH
Related in: MedlinePlus