Analysis of User-generated Content in Visitor Reviews of Tourist Attractions Using Semantic Similarity

Abstract

The tourism industry plays an important role in the world economic sector because it makes a significant contribution to the global economy, creates jobs, and strengthens economic growth. Therefore, visitor satisfaction is very important in this industry. Currently tourists use information in online media to find tourist attractions that suit their needs and expectations. Reviews of tourist attractions are growing on the internet. Customers can post reviews, recommendations, or ratings of a tourist spot. Online reviews in the form of User-generated Content (UGC) can provide benefits for business managers to obtain feedback from customers and improve certain product attributes or service characteristics in order to increase business value and support marketing activities. In this study, data collection will be carried out from one of the UGC tourism data sources, namely visitor reviews on Google Maps. Data analysis was performed using the natural language processing method. Analysis of these data will produce comprehensive information about tourist feedback.