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Topic Classification Method for Analyzing Effect of eWOM on Consumer Game Sales
April 23, 2019 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
Yoshiki Horii, Hirofumi Nonaka, Elisa Claire AlemΓ‘n CarreΓ³n, Hiroki Horino, Toru Hiraoka
arXiv ID
1904.13213
Category
cs.IR: Information Retrieval
Citations
0
Venue
arXiv.org
Last Checked
4 months ago
Abstract
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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