Visualization of Online-Game Players Based on Their Action Behaviors. (18th August 2008)

• Record Type: Journal Article
• Authors: Thawonmas, Ruck; Iizuka, Keita
• Other Names: Smed Jouni Academic Editor.
• Is Part Of: International journal of computer games technology. Volume 2008(2008)
• Publication Date: 2008-08-18
• Subjects: Computer games -- Design -- Periodicals; Computer games -- Programming -- Periodicals; Jeux d'ordinateur; Jeux d'ordinateur -- Programmation; Computer games -- Design; Computer games -- Programming; Electronic journals; Periodicals; 794.81
• DOI: 10.1155/2008/906931
• Languages: English
• ISSNs: 1687-7047

Abstract

Abstract : We propose a visualization approach for analyzing players' action behaviors. The proposed approach consists of two visualization techniques: classical multidimensional scaling (CMDS) and KeyGraph. CMDS is for discovering clusters of players who behave similarly. KeyGraph is for interpreting action behaviors of players in a cluster of interest. In order to reduce the dimension of matrices used in computation of the CMDS input, we exploit a time-series reduction technique recently proposed by us. Our visualization approach is evaluated using log of an online game where three-player types according to Bartle's taxonomy are found, that is, achievers, explorers, and socializers.