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Analysis of Emotional Tendency and Syntactic Properties of VR Game Reviews

  • Yang Gao
  • , Anqi Chen
  • , Susan Chi
  • , Guangtao Zhang
  • , Aimin Hao*
  • *Corresponding author for this work
  • Beihang University
  • NetEase Games
  • Technical University of Denmark

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publicationProceedings - 2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages648-649
Number of pages2
ISBN (Electronic)9781665484022
DOIs
StatePublished - 2022
Event2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2022 - Virtual, Online, New Zealand
Duration: 12 Mar 202216 Mar 2022

Publication series

NameProceedings - 2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2022

Conference

Conference2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2022
Country/TerritoryNew Zealand
CityVirtual, Online
Period12/03/2216/03/22

Keywords

  • Applied computing
  • Computer games
  • Computers in other domains
  • HCI design and evaluation methods
  • Human-computer interaction (HCI)
  • Humancentered computing
  • Personal computers and PC applications
  • User studies

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