# Emotional Contribution Analysis of Online Reviews

## TL;DR

This paper develops a cross-language market research tool analyzing emotional keywords from Chinese online reviews of Japanese hotels, using entropy-based models and machine learning to identify customer demands and emotions.

## Contribution

It introduces a novel method combining entropy-based analysis and machine learning to extract influential emotional keywords from online reviews across languages.

## Key findings

- Identified key emotional keywords in Chinese reviews of Japanese hotels.
- Demonstrated the effectiveness of the combined entropy and machine learning approach.
- Provided insights into customer demands and emotional drivers in the tourism industry.

## Abstract

In response to the constant increase in population and tourism worldwide, there is a need for the development of cross-language market research tools that are more cost and time effective than surveys or interviews. Focusing on the Chinese tourism boom and the hotel industry in Japan, we extracted the most influential keywords in emotional judgement from Chinese online reviews of Japanese hotels in the portal site Ctrip. Using an entropy based mathematical model and a machine learning algorithm, we determined the words that most closely represent the demands and emotions of this customer base.