ABSTRACT
There has been considerable interest in applying social network analysis methods to geographically embedded networks such as population migration and international trade. However, research is hampered by a lack of support for exploratory spatial-social network analysis in integrated tools. To bridge the gap, this research introduces a spatial-social network visualization tool, the GeoSocialApp, that supports the exploration of spatial-social networks among network, geographical, and attribute spaces. It also supports exploration of network attributes from community-level (clustering) to individual-level (network node measures). Using an international trade case study, this research shows that mixed methods --- computational and visual --- can enable discovery of complex patterns in large spatial-social network datasets in an effective and efficient way.
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Index Terms
- Spatial-social network visualization for exploratory data analysis
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