On this week's Journal Club session, Xinge Tong will talk about her PhD work in the presentation entitled "Exploring the Use of Online Reviews in the Development of Video Game".

It is now well established that online game reviews can play an important role in both reflecting game-player experiences and influencing business decisions regarding future video game development. Some studies have analysed different approaches to processing game reviews in the context of video game data development to assess their practical efficacy. However, most works in the field of game studies seem to rely on qualitative analysis approaches and software-related tools. These not only consume time and human resources but might also raise concerns about the difference in the focus of entertainment between software and games. The study described in this presentation sets out to explore the possibility of introducing natural language processing (NLP) into game review studies. It was noted that game reviews on Steam are a rich and valuable source. One of the main challenges of using NLP to process game reviews is how to extract effectively the diversity of meaning and accurately summarises the views of players. This study focuses on the accurate filtering of useful feedback information that is based on different contexts, the evaluation of user feedback, and the formulation of appropriate and effective game development strategies that incorporate this feedback. The main contribution of this study is the exploration and development of an NLP-based game review analysis system that: a) is able to process both topic and sentiment classification, b) makes highly accurate predictions and classifications to reviews by adopting advanced machine learning models with training on a newly produced game specific dataset, c) can be adopted and incorporated to the practical video game development lifecycle to process various tasks and meet developers’ diverse needs.

Date: 2025/04/11
Time: 14:00
Location: SP3011 & online