Network visualizations are commonly used to analyze relationships in various contexts. To efficiently explore a network visualization, the user needs to quickly navigate to different parts of the network and analyze local details. Recent advancements in display and interaction technologies inspire new visions for improved visualization and interaction design. Past research into network design has identified some key benefits to visualizing networks in 3D versus 2D. However, little work has been done to study the impact of varying levels of embodied interaction on network analysis. We present a controlled user study that compared four environments featuring conditions and hardware that leveraged different amounts of embodiment and visual perception ranging from a 2D visualization desktop environment with a standard mouse to a 3D visualization virtual reality environment. We measured the accuracy, speed, perceived workload, and preferences of 20 participants as they completed three network analytic tasks, each of which required unique navigation and substantial effort. For the task that required participants to iterate over the entire visualization rather than focus on a specific area, we found that participants were more accurate using a VR and a trackball mouse than conventional desktop settings. From a workload perspective, VR was generally considered the least mentally demanding and least frustrating in two of our three tasks. It was also preferred and ranked as the most effective and visually appealing condition overall. However, using VR to compare two side-by-side networks was difficult, and it was similar to or slower than other conditions in two of the three tasks. Overall, the accuracy and workload advantages of conditions with greater embodiment in specific tasks suggest promising opportunities to create more effective environments in which to analyze network visualizations.

翻译：网络可视化常被用于分析各种情境中的关系。为高效探索网络可视化，用户需快速导航至网络不同部分并分析局部细节。显示与交互技术的最新进展为改进可视化与交互设计提供了新思路。过往网络设计研究已发现三维可视化相较于二维的若干核心优势，但关于不同程度的具身交互对网络分析影响的研究尚属空白。我们开展了一项受控用户研究，比较了四种实验环境——这些环境结合不同硬件配置与条件，利用从二维桌面环境（标准鼠标）到三维虚拟现实环境的不同程度具身性与视觉感知。我们测量了20名参与者在完成三项网络分析任务时的准确率、速度、感知工作负荷及偏好，每项任务均需独特导航策略与大量操作投入。针对需遍历整个可视化区域而非聚焦特定区域的任务，我们发现使用VR与轨迹球鼠标的参与者较传统桌面环境具有更高准确率。从工作负荷角度而言，VR在三个任务中的两个被视为最不消耗脑力且最不令人沮丧。该条件在整体上也是用户首选，并被评为最有效且视觉吸引力最强的方案。然而，使用VR对比并排网络存在困难，且在三个任务中的两个任务中，其速度与其它条件相当或更慢。总体而言，具身性更强的条件在特定任务中展现的准确率与工作负荷优势，为创建更高效的分析网络可视化环境提供了重要契机。