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- W4387012908 abstract "Recent advances in virtual environments have extended real-life activities to virtual spaces, thereby generating enormous amounts of data on spatial behaviors. Spatial behaviors in physical spaces have been extensively studied; however, in virtual spaces, it is limited to measuring proxemic distances or visualizing spatial diffusion. Therefore, to understand users’ spatial behaviors in virtual spaces, a novel network approach that connects users and spaces is proposed in this study. Using a proxemics dataset from a virtual conference, positional connectivity between users and spatial units was measured using Euclidean and temporal measurements. A bipartite network and projections were used to extract Close-Proximity Interactions. The proposed method quantified user activities using topological features. In addition, log analysis revealed observations of spatial interactions in virtual spaces without a dedicated tool, such as an eye tracker. The results of this study can improve the understanding of remote-learning activities in virtual spaces. Its application can help education managers, designers, and marketers to assess user interactions based on specific contexts in virtual spaces." @default.
- W4387012908 created "2023-09-26" @default.
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- W4387012908 date "2023-09-26" @default.
- W4387012908 modified "2023-09-26" @default.
- W4387012908 title "Spatial Behavior Data in Virtual Conference: Proximity and Network Analysis" @default.
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- W4387012908 doi "https://doi.org/10.1007/978-981-99-2314-4_8" @default.
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