  Spatial Social Networks (SSN) build on the node and edge structure used in
Social Network Analysis (SNA) by incorporating spatial information. Thus, SSNs
include both topological and spatial data. The geographic embedding of the
nodes makes it impossible to move the nodes freely, rendering standard
topological algorithms (e.g. force layout algorithms) used in SNA ineffective
to visualize SSN sociograms. We propose a new visualization technique for SSNs
that utilize the spatial and social information to provide information about
the orientation and scale of connections. The donut visualization can be used
to summarize the entire network or can be used on a part of the network. We
demonstrate the effectiveness of the donut visualization on two standard SSNs
used in literature.
