GeoSocialVis: Visualizing geosocial academic co-authorship networks by balancing topology- and geography-based layout

Map with superimposed circles for individual authors and lines drawn between them to show coauthorship.
GeoSocialVis showing the IEEE Information Visualization (InfoVis) 2008–2018 geosocial co-authorship network. The visualization consists of the geosocial network visualization, the topology and geography balance slider, and the paper search panel. Node color encodes the author's most recent affiliation, size encodes paper count, and larger nodes are labeled with author initials
In many domains, it is important to understand both the topology and geography of a network. E.g., for researchers it is important to understand the topics in a field, where this research is taking place, and which researchers collaborate. Geography plays a key role in collaboration as it is more feasible with physical proximity. Researchers are also likely to continue existing collaborations. The interplay between topology and geography is of particular interest. Within-institution collaborations are different in nature from far-distance collaborations, as long-distance collaborations often occur less out of convenience but for more complementary expertise. These long-distance collaborations can connect otherwise separate social groups. However, existing approaches either focus on the geospatial location of researchers, or on the social aspect of collaborations alone. We present GeoSocialVis, an interactive visualization tool for scientometrics analyses with a focus on displaying the geosocial co-authorship network. GeoSocialVis uses a novel force layout that strikes a user-defined balance between showing network topology and the geographic locations of the authors. Users can explore relevant publications, researchers, groups, and institutions by adjusting the balance between topology and geography, searching by keywords, and with details-on-demand. We demonstrate the utility of GeoSocialVis with a case study with IEEE Information Visualization 2008–2018 publication data. Source code and an interactive demo are available online at
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