Top concerns of user experiences in Metaverse games: A text-mining based approach

• Published in: Entertainment computing Vol. 46; p. 100576
• Main Authors: Alma Çallı, Büşra, Ediz, Çağla
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.05.2023
• Subjects: Metaverse; Mobile gaming; Text mining; Topic modeling; User experience; Virtual worlds; Text mining; Topic modeling; Mobile gaming; User experience; Metaverse; Virtual worlds
• ISSN: 1875-9521; 1875-953X
• DOI: 10.1016/j.entcom.2023.100576

•We analysed low score user comments of mobile applications related to three commonly used Metaverse games (Minecraft, Roblox or Play Together) by using Topic Modelling with Latent Dirichlet Allocation.•As a result of Topic Modelling, we identified 12 topics, including social misconduct, controls, content lost, social interaction, price fairness, computing resources, support, playability, unstable connections, cheating, authorization, and bans.•Users were more frequently concerned about issues related to computing resources and price fairness.•The comments that users liked the most belong to the controls, content lost and scial interaction. Studies on game experience, which are the most typical representatives of the Metaverse, are conceptual and in their infancy. Previous work on virtual worlds and user experience is context-specific, and user experience changes over time. Literature using text mining in game experience studies is highly fragmented and focused on extracting adjectives for user reviews, which prevents anticipating the context. Considering Metaverse's unique concepts and content, developments in supporting technologies, and the ever-increasing mobility trend, it is essential to explore how the user experience is affected, especially in mobile virtual world applications. For this reason, user comments with low scores of mobile applications related to three commonly used Metaverse games (Minecraft, Roblox or Play Together) were analyzed. To the best of our knowledge, this is the first study attempting to extract user concerns associated with mobile applications of Metaverse games by using text mining. As s result, we identified 12 topics, including social misconduct, controls, content lost, social interaction, price fairness, computing resources, support, playability, unstable connections, cheating, authorization, and bans. The analysis further indicated users were more frequently concerned about issues related to computing resources and price fairness. Besides, the comments that users liked the most belong to the controls, content lost and social interaction.