Sound Similarity as a Tool for Understanding Player Experience: Applying Similarity Matrix to Gameplay Performance Segmentation

Abstract

Analytical accounts chronicling engagement with digital games can always benefit from empirical data outlining the patterns of behavior produced by different players as they engage with the same game, or similar sequence within a game. This paper presents an extension to a novel method, termed feedback-based gameplay metrics, which exploits the audio and visual output of an activated game to produce accounts of player performance. This paper offers an account of an affiliated method, based on similarity matrices, which is derived from the same measurement process and that has yet been applied to the interests of game studies (over design oriented research) to determine the similarity or diversity within encounters with particular games. This paper introduces the method and illustrates its potential applications in the analysis of performance.