소셜 빅데이터를 통한 코로나 전후 스키리조트 소비트렌드 분석

박진민; 오승욱; 한진욱

doi:10.35159/kjss.2022.6.31.3.451

주제분류

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저널정보

한국체육과학회
한국체육과학회지 학술저널
한국체육과학회지 제31권 제3호 (인문사회과학 편)
2022.6 451 - 463 (13page)
DOI : 10.35159/kjss.2022.6.31.3.451

저자정보

박진민 (경희대학교)
오승욱 (경희대학교)
한진욱 (경희대학교)

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초록·키워드

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The purpose of this study was to analyze consumption trend in ski resorts before and after COVID-19 using social big data. Toward this end, a big data solution, "TextoM" was utilized to crawl and analyze social text data related to ski resorts from NAVER, DAUM, and Google. Data analyses included text mining, sentiment analysis, and semantic network analysis. The results of this study were as follows. Firstly, the result of text mining indicated that ski and snowboard participants preferred taking a one-day ski trip to staying one or two nights at the ski resorts after COVID-19. In addition, safety-related keyword increased after COVID-19. Secondly, sentiment analysis revealed that negative emotion about ski resorts has been increasing since COVID-19 outbreak. Thirdly, network among ski resorts related keyword was loosen after COVID-19, indicating that ski and snowboard participant"s interest in ski resorts decreased. Discussions and additional practical implication were also suggested.

#consumption trend #ski resorts #COVID-19 #social big data