Emotional Contribution Analysis of Online Reviews
This work addresses the problem of efficient market analysis for the tourism industry, particularly in cross-language contexts, but it is incremental as it applies existing methods to a new dataset.
The study tackled the need for cost-effective cross-language market research tools by analyzing Chinese online reviews of Japanese hotels to identify keywords influencing emotional judgments, using an entropy-based model and machine learning to determine words representing customer demands and emotions.
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.