The Intersection of Virtual Reality and Art: Hotspots Analysis Based on Computer Science Clustering Algorithm
- DOI
- 10.2991/978-94-6463-046-6_50How to use a DOI?
- Keywords
- VR Art; Virtual Reality; Topic Modelling; Clustering Algorithm; Hotspots
- Abstract
VR art has received attention as the intersection of virtual reality and art. In order to understand the current research hotspots in VR art, we built a panorama of current research hotspots through a keyword co-occurrence analysis study based on topic modelling and computer science clustering algorithms. The data analysis resulted in three maps: Network Visualization, Overlay Visualization and Density Visualization. these three views allowed us to see how keywords are coupled, how keywords or hotspots change over time, how often they appear and how hot they are. In summary, the current research focus and direction of VR art is deep learning, machine learning and algorithms. Secondary directions relate to health and psychotherapy. the future of VR art depends on advances in virtual reality technology. Art exists as a secondary topic in the field of VR art, appearing more as an auxiliary tool.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Yiyuan Ding AU - Yaxiong Lei AU - Jiayu Zeng PY - 2022 DA - 2022/12/17 TI - The Intersection of Virtual Reality and Art: Hotspots Analysis Based on Computer Science Clustering Algorithm BT - Proceedings of the 2022 2nd International Conference on Computer Technology and Media Convergence Design (CTMCD 2022) PB - Atlantis Press SP - 419 EP - 428 SN - 2352-538X UR - https://doi.org/10.2991/978-94-6463-046-6_50 DO - 10.2991/978-94-6463-046-6_50 ID - Ding2022 ER -