Sentiment Analysis of Japanese Tourism Online Reviews

摘要

Purpose: Online reviews on tourism attractions provide important references for potentialtourists to choose tourism spots. The main goal of this study is conducting sentiment analysisto facilitate users comprehending the large scale of the reviews, based on the comments aboutChinese attractions from Japanese tourism website 4Travel.Design/methodology/approach: Different statistics- and rule-based methods are used toanalyze the sentiment of the reviews. Three groups of novel statistics-based methodscombining feature selection functions and the traditional term frequency-inverse documentfrequency (TF-IDF) method are proposed. We also make seven groups of different rulesbased methods. The macro-average and micro-average values for the best classificationresults of the methods are calculated respectively and the performance of the methods areshown.Findings: We compare the statistics-based and rule-based methods separately and comparethe overall performance of the two method. According to the results, it is concluded that thecombination of feature selection functions and weightings can strongly improve the overallperformance. The emotional vocabulary in the field of tourism (EVT), kaomojis, negativeand transitional words can notably improve the performance in all of three categories. Therule-based methods outperform the statistics-based ones with a narrow advantage.Research limitation: Two limitations can be addressed: 1) the empirical studies to verify thevalidity of the proposed methods are only conducted on Japanese languages; and 2) the deeplearning technology is not been incorporated in the methods.Practical implications: The results help to elucidate the intrinsic characteristics of theJapanese language and the influence on sentiment analysis. These findings also providepractical usage guidelines within the field of sentiment analysis of Japanese online tourismreviews.Originality/value: Our research is of practicability. Currently, there are no studies that focuson the sentiment analysis of Japanese reviews about Chinese attractions.