Spatial-social network visualization for exploratory data analysis

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.