Abstract—While the market investigation is important in
game software development, there is a problem that there is no
effective way to pursue the factor of user's software evaluation.
In this research, we paid attentions to corpus (electric existence
of documents) considered that the factor relationships about the
user's evaluation were expressed potentially as their opinions.
As the way to achieve this idea, we tried to extract useful
knowledge by using SEM and topic model for visual and
quantitative analysis process. As the related work, there are
several researches about Game software market using text
mining methods (LSI, or LDA). However, they have the problem
concerning to objectivity or explanations because the
relationships between topics are not defined based on technical
algorithms and expressed only as the frequency of the words
that constructs the topics. Experimental results showed that our
proposal process can extract effectively the topics that users pay
attentions when they evaluate the game software and we can
interpret it.
Index Terms—Causal analysis, factor expression, game
software, structural equation modeling, topic model,
hierarchical latent dirichlet allocation.
The authors are with Computer Science and Intelligent Systems,
Graduate School of Engineering, Osaka Prefecture University, 1-1
Gakuen-cho, Naka-ku, Sakai-City, Osaka, Japan (e-mail:
kunimoto@mis.cs.osakafu-u.ac.jp, saga@cs.osakafu-u.ac.jp).
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Cite: Rikuto Kunimoto, Hiroshi Kobayashi, and Ryosuke Saga, "Factor Analysis for Game Software Using Structural Equation Modeling with Hierarchical Latent Dirichlet Allocation in User’s Review Comments," International Journal of Knowledge Engineering vol. 1, no. 1, pp. 54-58, 2015.
