Online News Article Analytics: An Alternative Method to Explore Seasonal Issues in National Parks


  • Eunjung Yang University of Florida
  • Jinwon Kim University of Florida
  • Kyu-Won Sim Korea National Park Research Institute
  • Brijesh Thapa Oklahoma State University



national parks, seasonal issues, online news articles, data mining, topic modeling


Seasonality can affect the use of park resources and visitors’ experience in national parks. To understand seasonal issues, park managers have typically relied on survey-based studies that tend to be limited in sample sizes and data collection periods. The purpose of this study is to utilize online news article analytics as a complementary approach to find dynamic issues based on topic-modeling techniques in the context of South Korean national parks. A total of 12,994 online news articles were collected from a Korean search engine—NAVER. Results indicated common issues such as environmental degradation/protection, and visitor experience/ activity across all four seasons, along with distinctive issues for each season (e.g., fall foliage, park services, and protecting endangered species). Such findings can not only benefit managers in assisting the development of effective seasonal park management plans, but they can also promote visitors’ attention by providing dynamic seasonal issues in national parks.

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