• Smart Media Journal
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• v.12 no.8
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• pp.9-17
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• 2023

The development of information and communication technology and the improvement of the development and dissemination of smart devices have caused changes in the form of tourism, and the concept of smart tourism has since emerged. In this regard, researches related to smart tourism has been conducted in various fields such as policy implementation and surveys, but there is a lack of research on application reviews. This study collects Trip Advisor application review data in the Google Play Store to identify usage of the application and user satisfaction through Latent Dirichlet Allocation (LDA) topic modeling. The analysis results in four topics, two of which are positive and the other two are negative. We found that users were satisfied with the application's recommendation system, but were dissatisfied when the filters they set during search were not applied or that reviews were not published after updates of the application. We suggest more categories can be added to the application to provide users with different experiences. In addition, it is expected that user satisfaction can be improved by identifying problems within the application, including the filter function, and checking the application environment and resolving the error occurring during the application usage.

• The Journal of Bigdata
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• v.3 no.2
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• pp.51-57
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• 2018

The purpose of this study is to find a valid link between color and tourism experience. We analyzed color that extracted by Aerial photo by IRI Image Scale to find color image. As an indicator of the experience of tourism, a review of the Tripadvisor was selected and analyzed through text mining. Results using text mining results and IRI image scales were generally inconsistent. To identify problems with aerial photo, the results of the analysis using the representative photographs provided by the Tripadvisor in the same way were the same as before. This indicate that details are key of tourism than the image of the overall background. This study presents new research directions by combining color analysis studies with text mining.

• Knowledge Management Research
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• v.24 no.1
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• pp.99-126
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• 2023

As cultural background contributes members of society to recognize and behave in a specific direction, customers with different cultural backgrounds show various reactions even when they are provided with the same service. Previous studies have used the Hofstede cultural dimension to understand how hotel visitors' satisfaction varies with the provided service as per their cultural background. However existing research only considered the cultural background of the guests, and there are not many studies focused on the types of travel. Therefore, in this study, the travel types of hotel visitors are classified into business travel visitors and leisure tourism visitors, and analyzed the effect of Hofstede's cultural dimension on hotel selection attributes according to the styles of travel. In this study, we collected information on six cultural dimensions of Hofstede, and from TripAdvisor, a representative tourism platform, 204,261 optional attribute ratings for hotels in New York to investigate the satisfaction of hotel selection attributes. In conclusion, it is expected that this study will be able to identify which service attributes the customers of various cultures who visit hotels put emphasis in advance, and therefore provide suitable service accordingly.