This study aimed to analyze trends of solo travel through social media big data reflecting social phenomena on Jeju Island which is the most preferred region for solo travelers. For three years from January 1, 2016 to December 31, 2018, we collected text data including the keyword ‘Jeju Island solo travel’ from blog and cafes of Korea’s leading portal site NAVER and DAUM. The data were collected using TEXTOM and UCINET 6 was used for analysis of degree centrality, closeness centrality, betweenness centrality, eigenvector centrality and CONCOR. According to the results of analysis, the words such as ‘Jeju Island’, ‘travel’, ‘guest house’, ‘course’, ‘restaurant’, and ‘accommodation’ were shown as high frequencies. In addition, the words such as ‘cafe’, ‘sea’, and ‘photo’ except for common words were influential in the centrality analysis. And CONCOR analysis included five clusters of ‘selection attributes of solo travel’, ‘selection attributes of Jeju Island’, ‘selection attributes of accommodation’, ‘stage of planning a travel’, and ‘influencing factors to decision-making’. The study is differentiated in that it used social media big data instead of traditional research methods. Furthermore it reflects social phenomena, so there will be practical value in establishing a tourism marketing strategy.
ABSTRACT Ⅰ. 서론 Ⅱ. 이론적 배경 1. 나홀로 여행 2. 소셜 미디어와 빅데이터 3. 관광학 분야에서의 소셜 미디어 빅데이터 연구 Ⅲ. 연구설계 1. 데이터 수집 및 정제 2. 데이터 분석방법 Ⅳ. 분석결과 1. 검색어의 주요 연관 단어 빈도 2. 중심성 분석 3. CONCOR 분석 Ⅴ. 결론 참고문헌
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