Developing Better Video Game Classifications using Tangible Aspects of Games
Modern video game genres are confusing to non-gamers and often do not give an accurate idea about the content of the game. Even two games with the same genre label can be very different in their content. Therefore, it would be beneficial to both gamers and non-gamers if a new classification, which focuses on the tangible aspects of games, is developed. Previous research indicates that there are underlying similarities between certain games even if they belong to different genres. The goal of this study is to build on the past research and develop game dimensions, focusing on more tangible aspects of a game (e.g. the pace of gameplay), to be used to better classify games. Eight dimensions were developed: Speed, Narrative, Play Styles, Aesthetics, Social Interaction, Social Cooperation, Social Competition, and Completion. One hundred modern games and one hundred retro games were classified along these eight dimensions. The data was then analyzed, alongside the similarity between games data from previous research, using a spectral-clustering algorithm to obtain a similarity matrix i.e. a matrix that shows the similarity between games classified. The similarity matrix shows that there are both clusters of games on the similarity matrix, indicating new genres can be found when using these dimensions, and games which serve as bridges between clusters.