Using customer emotional experience from e-commerce for generating natural language evaluation and advice reports on game products

Hamdan Gani, Kiyoshi Tomimatsu

研究成果: Article同行評審

摘要

Investigating customer emotional experience using natural language processing (NLP) is an example of a way to obtain product insight. However, it relies on interpreting and representing the results understandably. Currently, the results of NLP are presented in numerical or graphical form, and human experts still need to provide an explanation in natural language. It is desirable to develop a computational system that can automatically transform NLP results into a descriptive report in natural language. The goal of this study was to develop a computational linguistic description method to generate evaluation and advice reports on game products. This study used NLP to extract emotional experiences (emotions and sentiments) from e-commerce customer reviews in the form of numerical information. This paper also presents a linguistic description method to generate evaluation and advice reports, adopting the Granular Linguistic Model of a Phenomenon (GLMP) method for analyzing the results of the NLP method. The test result showed that the proposed method could successfully generate evaluation and advice reports assessing the quality of 5 game products based on the emotional experience of customers.

原文English
頁(從 - 到)145-161
頁數17
期刊Journal of ICT Research and Applications
13
發行號2
DOIs
出版狀態Published - 2019

All Science Journal Classification (ASJC) codes

  • 電腦科學(全部)
  • 資訊系統與管理
  • 電氣與電子工程

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