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

2026-08-27

AI Summary

本文探讨了沉浸式环境中自我中心网络布局的设计与评估，通过设计四种布局并进行用户研究，解决了传统桌面环境中的视觉混乱问题。

Abstract

This paper explores design considerations for egocentric network layouts in immersive environments, providing fresh empirical insights that enhance egocentric network analysis. An egocentric network focuses on the topological and semantic relationships around a focal node (ego) and its neighboring nodes (alters), targeting local sub-networks rather than the whole network. Traditional desktop environments, limited by display constraints, often face visual clutter as node numbers grow. Building on recent findings that immersive environments enhance network analysis, we explore layouts tailored for these spaces. We begin by identifying essential design properties and dimensions for egocentric network layouts, taking into account the unique features of 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 design implications for future immersive egocentric network layouts.

Problem

• egocentric network
• immersive environments
• visual clutter
• network analysis

Innovation

• Immersive Environments
• Egocentric Network Layouts
• Visual Analytics
• User Study