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2025 Vol.67, Issue 2
Leveraging News Big Data to Detect Early Warning Signs of Natural Disasters

뉴스 빅데이터 기반 자연재해 전조 감지 분석

Min-Jin Kima
,
Won-Ho Namb†
,
Mi-Hye Yangc
,
Ji-Wan Leed
,
Taegon Kime
,
Jong-Won Dof
,
Kyusuk Youg
,
Seong-Joon Kimh
김 민진a
,
남 원호b†
,
양 미혜c
,
이 지완d
,
김 태곤e
,
도 종원f
,
유 규석g
,
김 성준h
aGraduate Student, School of Social Safety and Systems Engineering, Hankyong National University, Anseong, Republic of Korea
bAssociate Professor, School of Social Safety and Systems Engineering, Institute of Agricultural Environmental Science, National Agricultural Water Research Center, Hankyong National University, Anseong, Republic of Korea
cPh.D. Student, Department of Convergence of Information and Communication Engineering, Hankyong National University, Anseong, Republic of Korea
dSenior Officer, Water Resources Information Center, Han River Flood Control Office, Seoul, Republic of Korea
eAssistant Professor, Department of Smart Farm, Jeonbuk National University, Jeonju, Republic of Korea
fDeputy Director, Rural Research Institute, Korea Rural Community Corporation, Ansan, Republic of Korea (Visiting Researcher, University of California, Davis)
gResearch Engineer, US Department of Agriculture – Agriculture Research Service, United States
hProfessor, Division of Civil and Environmental Engineering, College of Engineering, Konkuk University, Seoul, Republic of Korea
†Corresponding author Tel.: +82-31-670-5137 Fax: +82-31-670-5139 E-mail: wonho.nam@hknu.ac.kr
2025. pp. 1-12
PDF XML Citation
Abstract

Identifying early warning signs of natural disasters is critical for mitigating vulnerability and enhancing disaster preparedness. While traditional disaster management often relies on numeric hydrometeorological data, a comprehensive approach should incorporate information on the impacts of disasters on human and environmental systems. This study explores the use of news big data to detect precursors of natural disasters by analyzing disaster-related keywords collected through web crawling from January to December 2022. Focusing on South Korea's 2022 natural disasters—including droughts, heat waves, and severe flooding—the study examines the timing and frequency of disaster-related news mentions across regions. A comparative analysis of news data and actual disaster occurrence timelines highlights the feasibility of using media coverage as a near real-time monitoring tool. Findings suggest that integrating news archives with scientific indices can enhance disaster response systems by improving real-time monitoring and situational awareness. This approach demonstrates the potential for leveraging big data to develop a robust disaster early warning and monitoring system.

Keywords
Big data
disaster monitoring
early warning systems
natural disaster
web crawling
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Information
  • Publisher :The Korean Society of Agricultural Engineers
  • Publisher(Ko) :한국농공학회
  • Journal Title :Journal of Korean Society of Agricultural Engineers
  • Journal Title(Ko) :한국농공학회논문집
  • Volume : 67
  • No :2
  • Pages :1-12
  • Received Date : 2024-07-23
  • Revised Date : 2024-11-22
  • Accepted Date : 2024-12-17
  • DOI :https://doi.org/10.5389/KSAE.2025.67.2.001
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