Abstract

EgoNav is a visual analytics system that characterizes egos based on the relationship structure of their egocentric networks and presents the results as a spatialization. An ego, or individual node in a network, is most closely related to its neighbors, and to a lesser degree, to its neighbor's neighbors. For example, in social networks, people are closely related to their friends and family. In financial networks, the affairs of borrowers and lenders are more closely tied to each other. In fact, the relationship structure surrounding an ego, or an egocentric network, can provide characteristic information about the ego itself. Using network motif analysis and dimensionality reduction techniques, the system places egos in similar areas of a spatialization if their egocentric networks are structurally similar. This view of a network discriminates between the various classes of typical and exceptional egos. We demonstrate its effectiveness using appropriate synthetic datasets, real-world mobile phone call and peer-to-peer lending datasets. We subsequently elicit user feedback from experts involved in the investigation of financial fraud to assess the tool's applicability in this domain.