Abstract

An ego-centric network describes the relationships between a particular node (ego) to its neighboring nodes (alters), so it is essential to present such network with good visualization. This work aims at introducing an efficient method, namely the Uniform Placement of Alters on Spherical Surface (U-PASS), to represent an ego-centric network so that all alters are scattered on the surface of the unit sphere uniformly. Unlike other simple uniformity that considers to maximize Euclidean distances among nodes, U-PASS is a three-stage method that spreads the alters with the consideration of existing edges among alters, no overlapping of node clusters, and node attribute information. Particle swarm optimization is employed to improve efficiency in node allocations. To guarantee the uniformity, we show the connection between our U-PASS to the minimum energy design on a two-dimensional flat plane with a specific gradient. We provide a demonstration on allocating nodes of an ego-centric network with 50 nodes, and some distance statistics show good performance of U-PASS when compared to four state-of-the-art methods via self-organizing maps and force-driven approaches.