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Visual Network Analysis in Immersive Environments: A Survey

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arxiv 2501.08500 v2 pith:7BC7OYOJ submitted 2025-01-15 cs.HC

classification cs.HC
keywords immersivedesignnetworkanalysisapplicationsenvironmentsvisualapproaches
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The increasing complexity and volume of network data demand effective analysis approaches, with visual exploration proving particularly beneficial. Immersive technologies, such as augmented reality, virtual reality, and large display walls, have enabled the emerging field of immersive analytics, offering new opportunities to enhance user engagement, spatial awareness, and problem-solving. A growing body of work has explored immersive environments for network visualisation, ranging from design studies to fully integrated applications across various domains. Despite these advancements, the field remains fragmented, lacking a clear description of the design space and a structured overview of the aspects that have already been empirically evaluated. To address this gap, we present a survey of visual network analysis in immersive environments, covering 138 publications retrieved through a structured pipeline. We systematically analyse the key aspects that define the design space, investigate their coverage in prior applications (n=87), and review user evaluations (n=59) that provide empirical evidence for essential design-related questions. By synthesising experimental findings and evaluating existing applications, we identify key achievements, highlight research gaps, and offer guidance for the design of future approaches. Additionally, we provide an online resource to explore our results interactively, which will be updated as new developments emerge.

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Cited by 1 Pith paper

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  1. A Design Study on Voice-based Interaction for Immersive Network Visualization and Analysis

    cs.HC 2026-07 conditional novelty 6.0 of 10

    Voice-primary, LLM-driven command input can make immersive network visualization feel more usable and less cognitively demanding than controller-based interaction, according to a qualitative user study.

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