Abstract: The secondary and derivative effects of natural disasters have significant impacts on the economy and society, making it urgent to research the disaster chains mechanisms. This study utilized web scraping software to collect news reports based on text rules. Through data cleaning, extraction, and encoding to analyze the evolution model, overall, time, and spatial characteristics of the natural disaster chain in Northwest China. The results indicate that the natural disaster chain in Northwest China can be classified into four evolution models: linear, divergent, centralized, and cross. Different models of disaster chains cause different disaster losses. Rainstorm disasters have the highest concurrency, while low-temperature disasters have the highest continuity. Between 2017 and 2023, there was a trend of increasing and then decreasing numbers of disasters and disaster chains, while the length of disaster chains showed a pattern of decreasing and then increasing. Summer experienced the largest number of disasters and disaster chains, while spring and winter had the longest disaster chain. Gansu and Shanxi are the regions with the highest risk. This study enhances the research findings on disaster chains, which provides decision-making references for disaster risk assessment and emergency management in Northwest China under the framework of big data analysis.

Keywords: Natural disasters; disaster chain; news report; evolution model; spatiotemporal characteristics

基金资助：This work was supported by the [Major Program of National Fund of Philosophy and Social Science of China] under Grant [21&ZD162]; and [Innovation Star Project for Graduate Students in Gansu Province, China] under Grant [2025CXZX-031]; and [Fundamental Research Funds for the Central Universities] under Grant [2023lzujbkyxs025].

原文链接：https://doi.org/10.1080/19475705.2025.2521652