텍스트 마이닝을 활용한 산림 공공애플리케이션의 보완 및 개선 연구
A Study on the Supplementation and Improvement of Forest Public Applications Using Text Mining Analysis
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초록
기후변화로 인하여 산불·산사태 등과 같은 산림 재해가 증가하고 그 피해 규모도 점점 커지고 있다. 이와 동시에 산림복지서비스에 대한 사회적 수요도 지속적으로 증가하고 있는 실정이다. 이러한 상황에 대응하기 위해 산림청에서는 효과적인 재해방지와 복지서비스의 구현을 위한 모바일 애플리케이션으로 산림 재해경고 및 신고서비스인 ‘스마트 산림재난’과 산림복지서비스 플랫폼인 ‘숲나들e’를 제공하고 있다. 본 연구는 두 애플리케이션에 대한 사용자 평가와 리뷰를 대상으로 텍스트 마이닝 기법으로 분석하여, 현재 운용상의 문제점을 파악하고 개선 및 발전 방안을 제시하는 것을 목표로 수행하였다. 분석 대상 자료는 주요 앱스토어 2곳(구글 플레이스토어, 애플 앱스토어)에서 수집한 총 454건(‘스마트 산림재난’ 49건, ‘숲나들e’ 405건)으로 이를 바탕으로 TF-IDF와 감성분석을 실시하였다. 분석 결과, ‘스마트 산림재난’ 앱은 신고 기능과 신고처리 과정에 대한 보완이 필요한 것으로 나타났으며, ‘숲나들e’는 시스템 안정성과 신뢰성을 높이기 위한 전반적인 개선이 요구되는 것으로 확인되었다.
Abstract
As forest disasters such as forest fires and landslides increase due to climate change, and social demand for forest recreation and welfare services increases, the Korea Forest Service provides forest disaster warning and prevention (Smart Forest Disaster) and forest recreation and welfare (Forest Outing e) services through mobile applications. This study identified problems and suggested improvement and development plans through text mining analysis of user evaluations and reviews of these public applications. The target data of the analysis were 454 cases (49 cases of "Smart Forest Disaster" and 405 cases of "Forest Outing e") imported from two major app stores (Google Play Store and Apple App Store), and TF-IDF and sentiment analysis were performed on them. As a result, it was found that the 'Smart Forest Disaster' app needed to supplement the reporting function, and 'Forest Outing e' needed overall improvement to increase system stability and reliability.
참고문헌 (21)
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