title: A geovisual analytic approach to understanding geo-social relationships in the international trade network.
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.
authors.affiliation: GeoVISTA Center, Department of Geography, Pennsylvania State University, University Park, Pennsylvania, United States of America.
authors.forename: Wei
authors.initials: W
authors.lastname: Luo
authors.affiliation: PDA Group, Department of Computer Science & Engineering, Pennsylvania State University, University Park, Pennsylvania, United States of America.
authors.forename: Peifeng
authors.initials: P
authors.lastname: Yin
authors.affiliation: Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America.
authors.forename: Qian
authors.initials: Q
authors.lastname: Di
authors.affiliation: GeoVISTA Center, Department of Geography, Pennsylvania State University, University Park, Pennsylvania, United States of America.
authors.forename: Frank
authors.initials: F
authors.lastname: Hardisty
authors.affiliation: GeoVISTA Center, Department of Geography, Pennsylvania State University, University Park, Pennsylvania, United States of America.
authors.forename: Alan M
authors.initials: AM
authors.lastname: MacEachren
mesh_terms: D003132:Commerce; D003196:Computer Graphics; D005843:Geography; D038622:Internationality; D007398:Interpersonal Relations; D009010:Monte Carlo Method; D062206:Spatial Analysis