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.