The Big Data-Based Analysis on Climate Change and Natural Disaster and Its Implications

Abstract

This paper aims to analyze key issues and characteristics of environmental policy over time through big data-based analysis on climate change and natural disasters. To achieve this, articles from 1900 to August 2022 are extracted and text mining analysis is conducted. Methodologically, text mining is a tool for extracting useful information from electronic (Documents Text Data) such as web pages, and is used in various ways such as extracting major (Keywords Word Cloud), network analysis, and topic analysis. In this study, it is analyzed through word cloud analysis and simultaneous network analysis through simple frequency analysis. The results show that the frequency of natural disasters caused by climate change has been highly increasing, and the damages are caused mainly by localized torrential rains. It implies that natural disaster damage caused by climate change are diversifying, so that countermeasures should be prepared to reduce future damages related to climate change.