Topic Classification Method for Analyzing Effect of eWOM on Consumer Game Sales
Information Retrieval
2019-05-14 v1
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.
Keywords
Cite
@article{arxiv.1904.13213,
title = {Topic Classification Method for Analyzing Effect of eWOM on Consumer Game Sales},
author = {Yoshiki Horii and Hirofumi Nonaka and Elisa Claire Alemán Carreón and Hiroki Horino and Toru Hiraoka},
journal= {arXiv preprint arXiv:1904.13213},
year = {2019}
}
Comments
arXiv admin note: substantial text overlap with arXiv:1904.11797, arXiv:1904.12039, 1904.13214