  Electronic word-of-mouth (eWOM) has become an important resource for the
analysis of marketing research. In this study, in order to analyze user needs
for consumer game software, we focus on tweet data. And we proposed topic
extraction method using entropy-based feature selection based feature
expansion. We also applied it to the classification of the data extracted from
tweet data by using SVM. As a result, we achieved a 0.63 F-measure.
