Evaluating Acceptance of Video Games using Convolutional Neural Networks for Sentiment Analysis of User Reviews

Video game and interactive media are currently among the most profitable industries in the world. In this competitive marketing, game producers are interested in designing products with aspects that increase user acceptance, such as a well written story, stable servers for multiplayer games, and fluid combat mechanics. Although user-expressed feelings about game aspects seem to correlate with user acceptance, sentiment analysis is under-exploited for video games user acceptance evaluation. In this poster, we propose an approach to evaluate the user acceptance of video games by using convolutional neural networks for aspect-based sentiment analysis of user text reviews.