텍스트 마이닝을 이용한 관광지 이미지 구성요인 및 측정에 관한 연구

Abstract

The purpose of this study is to examine the components of tourist destination image and its measurement through travelers’ on-line review data using a well-known travel site, and to withdraw implications for constructing a competitive destination image according to different types of tourist destinations. In order to extract lively and realistic information from travelers about destination image, this study collected travelers’ reviews on a travel community website, and analyzed them using the text miming approach. This is an appropriate analytic method for examining qualitative data from SNS and Big Data in the operating environment of Web 2.0. A web crawling method was used to collect the appropriate samples and to analyze travelers’ opinion data from the selected travel community website, Tripadvisor.com. The collected data of qualitative information from travelers’ online reviews was converted into a quantitative form that was available for statistical analysis using text mining and TF-IDF(Term Frequency-Inverse Document Frequency). The result showed that identifying the travelers’s perceived image of tourist destinations using reviews from online travel community would be a useful approach to provide meaningful implications for understanding tourist destinations’ image and developing competitive marketing strategies for the destinations. Another contribution of this study is to organize the quantitative analysis by extracting and processing the data from an online review that is basically qualitative data. Finally, this study provides the theoretical basis to apply Big Data in the tourism field, which increases exponentially on the internet and mobile environment through the advancement of travelers’ information technologies.