Understanding Player Experience Through the Use of Similarity Matrix

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 the novel method previously introduced in Marczak et al. (2013; 2015) and Schott et al. (2014), termed feedback-based game 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 matrix, 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.