Lie Detection in Social VR Using Multimodal Data

Trust is a key element in human relationships and is vital for the success of any interaction. Establishing trust in Social VR is important for promoting collaboration, communication, and social interaction. In our research, we investigate the feasibility of using lie detection techniques in virtual reality to build trust. Our findings suggest that it is possible to detect deception in virtual reality using sensor-detected cues. Using random forest, gaze-based features by themselves could reach an 87% accuracy in detecting lies.

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Published
2025-03-08
DOI
https://doi.org/10.1109/vrw66409.2025.00283
Primary Topic
Anomaly Detection Techniques and Applications
Type
article
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article

Lie Detection in Social VR Using Multimodal Data

Pan Hui, Ahmad Alhilal, C. Cheung, Zhizhuo Yin et al.
Anomaly Detection Techniques and Applications
article

Lie Detection in Social VR Using Multimodal Data

Pan Hui, Ahmad Alhilal, C. Cheung, Zhizhuo Yin, Reza Hadi Mogavi, Kriti Agrawal
article en

Abstract

Trust is a key element in human relationships and is vital for the success of any interaction. Establishing trust in Social VR is important for promoting collaboration, communication, and social interaction. In our research, we investigate the feasibility of using lie detection techniques in virtual reality to build trust. Our findings suggest that it is possible to detect deception in virtual reality using sensor-detected cues. Using random forest, gaze-based features by themselves could reach an 87% accuracy in detecting lies.

University of Waterloo (CA), Hong Kong University of Science and Technology (HK), Birla Institute of Technology and Science, Pilani - Goa Campus (IN), Aalto University (FI)
Reduced inequalities
Openalex Percentile: Top 96%
Anomaly Detection Techniques and Applications
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Lie Detection in Social VR Using Multimodal Data — Pan Hui, Ahmad Alhilal, et al. · (2025) | TGRS Research Map | TGRS