빅데이터를 활용한 휴양림 이용객현황과 인터넷 검색어의 상관관계분석
Correlation Analysis with Volume of Recreational Forest Visitors and Internet Search Words Using ‘Big Data’
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초록
본 연구는 휴양림을 찾는 이용객들의 수요를 관련 트렌드데이터와 검색어를 이용하여 사전에(Proactive) 예측하고, 미리 대비할 수 있는 방안을 찾아보기 위해, 구글과 네이버에서 제공하는 트렌드 데이터를 이용하여, 상관관계를 분석하였다. 상관관계분석결과 , 캠핑인구가 꾸준히 증가하는 추세를 반영하듯 이용객현황과 강한 상관관계를 가지는 검색어들로 구글트렌드 데이터를 이용했을 때는 ‘휴양림’과 ‘캠핑관련용어들’이수요예측에 적합한 것으로 나타났으며, 데이터 이용 시 같은 달 데이터를 비교하는 것이 가장 정확한 예측치를산출할 수 있을 것으로 예상되며, 네이버트렌드 모바일 데이터를 이용하였을 때는 같은 달 데이터 보다는 한· 두 달 전 데이터와 강한 상관관계를 보인 ‘휴양림’과 다른 조합의‘캠핑관련용어들’을 이용하여 예측치를 추정하는 것이 가장 합리적인 방법으로 나타났다.
Abstract
Big data, Google Trends and Naver Trends Mobile data, was used to find out how to prepare and manage recreational forests. Volume of recreational forest visitors and residents are good indicators to decide long and/or short term policy. Therefore, Person correlation analysis was employed to test for the relationship between volume of recreational forest visitors and internet search words. In this study, meaningful results were found through the process. Results of correlation analysis between Google Trends data and Visitors pattern data showed that Recreational Forests’ and ‘Camping related search words’were strongly correlated with trend data of the same month or one month ago. Results of correlation analysis between Naver Trends Mobile data and visitors pattern data also showed that ‘Recreational Forests’ and different combination of‘Camping related search words’ were strongly correlated. In this case, one or two months delayed visitors pattern data were resulted in better and stronger correlation than data of the same month. These search words can be used as variables in the forecasting volume of recreational forest visitors and residents.
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