The purpose of this study was to extract and analyze the extensive review data of tourists accumulated on the Tripadvisor travel community website to identify the restaurant selection attributes and preference factors of foreign tourists, and to derive meaningful results. In order to identify restaurant selection attributes and important preference factors in online reviews generated by restaurant customers, data was refined through text mining techniques and text network analysis was performed to reveal the structural with restaurant selection attributes. For the texts extracted by crawling, a frequency matrix was created by the word frequency list and key words using the TEXTOM program. Also, using Netdraw programs, visualized the results of the sementic network analysis and centreality of the extracted words and the structural equivalence of the words. As a result of the analysis, food, restaurant, good, place, korean, seoul, try, service and great words were found to be the main attributes in frequency and centrality. Additionally the attributes were categorized atmosphere, value, purpose and food by CONCOR analysis. Based on these findings, I would like to present theoretical and practical implications for market segmentation and marketing strategies to the restaurant industry.
목차
ABSTRACT Ⅰ. 서론 Ⅱ. 이론적 배경 1. 레스토랑 선택속성 2. 레스토랑 선호도 3. 레스토랑 온라인 리뷰 Ⅲ. 연구설계 1. 분석 자료의 수집 2. 분석방법 및 절차 Ⅳ. 성과분석 1. 데이터 수집 결과 2. 데이터 분석결과 Ⅴ. 결론 참고문헌
키워드
Big dataText MiningSelection AttributesCustomer PreferenceRestaurant Review
관광경영학을 실용학문의 체계로 확립하고 실천학문으로 정착시키기 위하여, 관광경영학문을 현실적응에 필요한 연구를 통해 국가관광정책의 방향을 제시하고, 관광사업자들에게는 실질적으로 도움이 되는 경영전략을 제공하며, 연구를 통하여 회원간의 친목도모와 정보교환을 함으로써 상호발전을 목적으로 한다.