Text Mining Approach to Improve Mobile Role Playing Games Using Users' Reviews

Abstract

The genre characteristics of RPG (role-playing game), which have high expectations for high sales and continuous profit generation, have created a phenomenon that has attracted many developers to become interested in the RPG market. However, recently, RPG development has been mass-produced that includes similar content, sensational advertisements, low quality, and excessive billing induction, which have negatively affected the game market and users' gameplay experiences. In this regard, we conduct a big data analysis on the users' reviews to find out what will be needed to have a positive gaming experience for mobile RPGs. User reviews are collected in the Google Play Store and analyzed to find ways to improve mobile RPG gameplay. In order to extract meaningful information from the collected big data, we use text mining techniques of topic modeling with an LDA algorithm to visualize the data. We propose a text mining approach as a practical method for better design of mobile RPGs since it analyze users' reviews and objectively grasps their opinions based on their gameplay. The results can be used to develop the mobile RPGs that can be played continuously by.