학술논문

Analysis of Emotional Tendency and Syntactic Properties of VR Game Reviews

Document Type

Conference

Author

Gao, Yang; Chen, Anqi; Chi, Susan; Zhang, Guangtao; Hao, Aimin

Source

2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW) VRW Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), 2022 IEEE Conference on. :648-649 Mar, 2022

Subject

Computing and Processing
General Topics for Engineers
Robotics and Control Systems
Signal Processing and Analysis
Solid modeling
Three-dimensional displays
Cybersickness
Conferences
Design methodology
Games
Syntactics
Applied computing—Computers in other domains—Personal computers and PC applications—Computer games
Humancentered computing—Human-computer interaction (HCI)—HCI design and evaluation methods—User studies

Language

Abstract

The studies of player reviews can help game developers design and optimize VR games. To this end, we investigated 288,685 reviews from 506 VR games on the Steam platform to analyze their sentiment tendencies using the machine learning-based model SKEP, which finds that although some of the reviews are “recommend”, they actually have opposite emotional tendencies. We also study the syntactic properties based on the natural language processing (NLP) kits Stanza and NLTK library, and we find that cybersickness is a significant concern for players.

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