Transformer Language Models for UX Dimensions in VR Gaming
Description
This repository contains seven fine-tuned transformer models for analyzing UX dimensions in virtual reality (VR) gaming. The models are based on RoBERTa-large [1] and were fine-tuned on 2,100 VR game reviews to classify sentiment across seven UX dimensions: Immersion, Presence, Achievement, Engagement, Embodiment, Physical Discomfort, and Controllability. Each model assigns one of three possible sentiment labels to user reviews: 0 (neutral): The UX dimension is mentioned neutrally or not discussed. 1 (positive): The UX dimension is described positively. 2 (negative): The UX dimension is described negatively. These models were developed as part of the research study: Pasch, S., Lee, S., Cha, M.C. (2025). Exploring UX Dimensions and Experience-Levels in VR Gaming: Insights from Online Reviews using Transformer Models. Citation: Please cite the corresponding research paper when using these models in your work. Additional References: [1] Liu, Y., Ott, M., Goyal, N., Du, J., Joshi, M., Chen, D., ... & Stoyanov, V. (2019). RoBERTa: A robustly optimized BERT pretraining approach. arXiv preprint arXiv:1907.11692.
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Institutions
- Hankuk University of Foreign Studies
Categories
Funders
- Hankuk University of Foreign Studies Research Fund