Paper Number
ECIS2025-1810
Paper Type
CRP
Abstract
The increasing accessibility of Virtual Reality (VR) applications leads to the emergence of novel products and services, especially in the context of interacting with applicants, consumers or employees. Technological developments such as eye- or body-tracking enable new analytical insights about team interaction or customer relationship formation, causing organizational and academic interest. However, conceptual and technical frameworks that effectively integrate multimodal data of spatial virtual environments are still lacking. To close this gap, we bring together a systematic literature review of scientific VR experiments with a cross-case analysis of organizational social VR application scenarios and reflective expert interviews. We reveal and conceptualize the important data category of virtual sensors. We outline how such virtual sensors are useful for augmenting physiological data and ex-post perception surveys of social VR experiences to offer a systematic and effective approach to study virtual social interactions in immersive environments.
Recommended Citation
Rose, Robert; Stosch, Lennart; and Trier, Matthias, "Analyzing Social Dynamics In Virtual Reality: Towards a Data-Driven Framework" (2025). ECIS 2025 Proceedings. 3.
https://aisel.aisnet.org/ecis2025/hci/hci/3
Analyzing Social Dynamics In Virtual Reality: Towards a Data-Driven Framework
The increasing accessibility of Virtual Reality (VR) applications leads to the emergence of novel products and services, especially in the context of interacting with applicants, consumers or employees. Technological developments such as eye- or body-tracking enable new analytical insights about team interaction or customer relationship formation, causing organizational and academic interest. However, conceptual and technical frameworks that effectively integrate multimodal data of spatial virtual environments are still lacking. To close this gap, we bring together a systematic literature review of scientific VR experiments with a cross-case analysis of organizational social VR application scenarios and reflective expert interviews. We reveal and conceptualize the important data category of virtual sensors. We outline how such virtual sensors are useful for augmenting physiological data and ex-post perception surveys of social VR experiences to offer a systematic and effective approach to study virtual social interactions in immersive environments.
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