Work

Surrounded by Friends: Design and Evaluation of Immersive Layouts of Egocentric Network for Visual Analytics

Year: 2026

Type: conference-paper

Abstract: Egocentric networks focus on a focal node (ego) and its neighboring alters, emphasizing local sub-networks rather than the whole graph. On traditional desktops, such visualizations suffer from clutter as networks grow, whereas immersive environments offer added spatial depth and embodied interaction. We explore how to design egocentric network layouts for these spaces. We first identify essential design properties and dimensions tailored to immersive environments. Based on these, we design four layouts–Cube, Cylindrical, Radial, and Spherical–that vary across design dimensions. We evaluate these layouts in a user study with 24 participants completing egocentric analysis tasks. Our study suggests that Cube performed well for tasks focused on ego-alter connection strength. In contrast, Spherical was more effective for understanding alter topology, minimizing occlusion, and efficiently utilizing 3D space. These findings inform the design of future immersive egocentric network layouts.

Source: ACM Symposium on Spatial User Interaction (SUI)

DOI: 10.1145/3822518.3830041

Authors: Kentaro Takahira, Takanori Fujiwara, Wong Kam-Kwai, Kento Shigyo, Leni Yang, Hiroaki Natsukawa, Yalong Yang, Huamin Qu

Institutions: Hong Kong University of Science and Technology, University of Arizona, Centre National de la Recherche Scientifique, Institut national de recherche en sciences et technologies du numérique, Osaka Seikei University, Georgia Institute of Technology

Language: English

Topic: Data Visualization and Analytics

Subfield: Computer Graphics and Computer-Aided Design

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W7204568174

FWCI:

Cites: 59

Cited by:

Related to: 10