期刊名称：International Journal of Computer Games Technology
印刷版ISSN：1687-7047
电子版ISSN：1687-7055
出版年度：2008
卷号：2008
DOI：10.1155/2008/906931
出版社：Hindawi Publishing Corporation
摘要：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.
