텍스트 마이닝을 활용한 산림 공공애플리케이션의 보완 및 개선 연구

A Study on the Supplementation and Improvement of Forest Public Applications Using Text Mining Analysis
  • 성준경
  • 박윤서
  • 윤화영
  • 양봉숙
  • 강규영

초록

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.

키워드

산림 애플리케이션스마트 산림재난숲나들e텍스트마이닝TF-IDFforest applicationSmart Forest DisasterForest Outing etext miningTF-IDF
제목
텍스트 마이닝을 활용한 산림 공공애플리케이션의 보완 및 개선 연구
제목 (타언어)
A Study on the Supplementation and Improvement of Forest Public Applications Using Text Mining Analysis
저자
성준경박윤서윤화영양봉숙강규영
DOI
10.14251/crisisonomy.2024.20.10.15
발행일
2024-10
저널명
Crisisonomy
20
10
페이지
15 ~ 27