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http://dx.doi.org/10.15813/kmr.2022.23.1.010

Sentiment Analysis and Star Rating Prediction Based on Big Data Analysis of Online Reviews of Foreign Tourists Visiting Korea  

Hong, Taeho (Pusan National University College of Business Administration)
Publication Information
Knowledge Management Research / v.23, no.1, 2022 , pp. 187-201 More about this Journal
Abstract
Online reviews written by tourists provide important information for the management and operation of the tourism industry. The star rating of online reviews is a simple quantitative evaluation of a product or service, but it is difficult to reflect the sincere attitude of tourists. There is also an issue; the star rating and review content are not matched. In this study, a star rating prediction model based on online review content was proposed to solve the discrepancy problem. We compared the differences in star ratings and sentiment by continent through sentiment analysis on tourist attractions and hotels written by foreign tourists who visited Korea. Variables were selected through TF-IDF vectorization and sentiment analysis results. Logit, artificial neural network, and SVM(Support Vector Machine) were used for the classification model, and artificial neural network and SVR(Support Vector regression) were applied for the rating prediction model. The online review rating prediction model proposed in this study could solve inconsistency problems and also could be applied even if when there is no star rating.
Keywords
Online review; Star rating; Sentiment analysis; Big data; Prediction model;
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