arXiv:1904.13213

Topic Classification Method for Analyzing Effect of eWOM on Consumer Game Sales

Yoshiki Horii, Hirofumi Nonaka, Elisa Claire Alemán Carreón, Hiroki Horino, Toru Hiraoka

제출 2019-04-23

원문 초록

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.

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