Identifying the skeptics and the undecided through visual cluster analysis of local network geometry

Abstract

By skeptics and undecided we refer to nodes in clustered social networks that cannot be assigned easily to any of the clusters. Such nodes are typically found either at the interface between clusters (the undecided) or at their boundaries (the skeptics). Identifying these nodes is relevant in marketing applications like voter targeting, because the persons represented by such nodes are often more likely to be affected in marketing campaigns than nodes deeply within clusters. So far this identification task is not as well studied as other network analysis tasks like clustering, identifying central nodes, and detecting motifs. We approach this task by deriving novel geometric features from the network structure that naturally lend themselves to an interactive visual approach for identifying interface and boundary nodes.

Keywords

• Graph/network data
• High dimensional data visualization
• Visualization in social and information sciences
• Data clustering coordinated and multiple views