Understanding social interaction in VR remote collaborative work

Abstract

Virtual Reality technology has transformed digital interactions by providing immersive experiences that mimic real-world engagement. Its application in remote collaborative work enables individuals across different locations to interact and collaborate within shared virtual spaces. Such collaborations' success heavily depends on the quality of social interaction within these virtual environments. This thesis investigated the user experience of social interaction in VR, aiming to understand its characteristics and explore methods to enhance it within the context of VR remote collaborative work.
The thesis begins by reviewing theoretical approaches to social interaction in VR and user experience theories (Chapter 2) and outlines research methods encompassing quantitative and qualitative analyses (Chapter 3). Chapter 4 reports on an experiment comparing user experience in VR with other communication forms. The results found that VR resulted in lower social presence and engagement than face-to-face communication. Furthermore, I have constructed a structural model that outlines the dynamics of social interaction in remote work settings. This model emphasizes the role of social presence in promoting engagement, empathy, and a deeper sense of immersion.
Chapter 5 presents interview findings exploring the characteristics and challenges of social interaction in VR remote collaboration. The characteristics were categorized into three groups: emotional and information transfer, social behavior, and task completion. The lack of mutual awareness and empathy emerged as the main obstacle hindering social interaction within VR environments. Additionally, participants reported experiencing cybersickness, which negatively impacted their VR experience. Therefore, in the following chapters, the thesis will focus on visualizing cybersickness to improve information exchange and collaboration.
Chapter 6 focuses on quantifying VR cybersickness by applying physiological measurements and machine-learning techniques. This study also demonstrates the potential of using multi-sensory physiological data to investigate, detect, and predict cybersickness.
Chapter 7 outlines the design process of a VR biofeedback system aimed at monitoring cybersickness while fostering social interaction in remote collaboration. Chapter 8 evaluates the impact of this novel biofeedback system on user experience using the structural model of social interaction during remote collaborative work. Participants in the biofeedback groups reported greater awareness of their partner's physical state and social cues than those in the no-feedback group. They also experienced enhanced social interactions and better user experience, especially in avatar-based feedback.
Finally, Chapter 9 concludes the thesis by providing the contributions made by this research and suggesting potential areas for future studies. Overall, the thesis identifies the challenges in VR social interaction and the development and assessment of a biofeedback system designed to enhance social interaction. These findings offer valuable guidance for designing and optimizing VR experiences in remote collaborative settings.

Date of Award	13 Jul 2025
Original language	English
Awarding Institution	University of Nottingham
Supervisor	Xu Sun (Supervisor), Haonan Li (Supervisor) & Canjun Yang (Supervisor)