Problem
Research questions and friction points this paper is trying to address.
immersive network visualization
voice-based interaction
visual network analysis
user interface affordance
multimodal interaction
A Design Study on Voice-based Interaction for Immersive Network Visualization and Analysis
🤖 AI Summary
This work addresses the limited accessibility of immersive network visualization due to complex interaction paradigms by proposing a novel voice-based interaction system powered by large language models (LLMs). For the first time, natural language is leveraged as the primary interaction modality within immersive environments for network visualization. Through a Research through Design (RtD) approach, the system integrates speech recognition, LLMs, and immersive visualization technologies to enable users to perform complex, multi-parameter analytical operations via spoken natural language, substantially reducing cognitive load. User studies demonstrate that, compared to traditional controller-based interactions, this approach significantly enhances perceived usability and facilitates more fluent articulation of analytical intent, particularly benefiting data analysis tasks in social and computer sciences.
📝 Abstract
Visual network analysis leverages network visualization authoring techniques to facilitate sensemaking, serendipitous discovery, and hypothesis verification on network data. However, transferring the same paradigm to immersive environments is non-trivial due to insufficient UI affordance for authoring operations. Researchers have studied combining multiple modalities for interactions, but the high learning curve of such input systems limits their adoption by typical data analysts, let alone for network analytics. In this work, we investigate the advantages and limitations of voice as the primary input modality with a research-through-design (RtD) study, in which we design a system that supports voice-based interactions for immersive network visualization facilitated by Large Language Models (LLMs). Through a user study on social network data analysis with participants from social science and computer science backgrounds, we find that voice interactions can improve perceived usability relative to controller-based interaction and lower the cognitive effort of formulating commands, since users can express intent in natural language rather than compressing it into terse instructions. We discuss design implications for immersive visualizations, highlighting how usability limits adoption while simplified interactions and voice-based controls enhance fluidity and support complex, multi-parameter operations.
Innovation
Methods, ideas, or system contributions that make the work stand out.
voice-based interaction
immersive visualization
large language models
network analysis
natural language interface
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