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International Journal of Computer Games Technology
Volume 2008, Article ID 906931, 9 pages
Research Article

Visualization of Online-Game Players Based on Their Action Behaviors

1Intelligent Computer Entertainment Laboratory, Graduate School of Science and Engineering, Ritsumeikan University, Kusatsu, Shiga 525-8577, Japan
2Solution Development Team, Solution Development Department, Bandai Networks Co., Ltd., Tokyo 111-8081, Japan

Received 1 February 2008; Revised 8 May 2008; Accepted 11 June 2008

Academic Editor: Jouni Smed

Copyright © 2008 Ruck Thawonmas and Keita Iizuka. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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.