Discovering the relationship of disasters from big scholar and social media news datasets
The construction method for chains of disasters or events is still one of the core scientific questions in studying the common rules of disaster’s evolution. Especially when dealing with the complexity and diversity of disasters, it is critical to make a further investigation on reducing the dependency of prior knowledge and supporting the comprehensive chains of disasters. This paper tries to propose a novel approach, through collecting the big scholar and social news data with disaster-related keywords, analysing the strength of their relationships with the co-word analysis method, and constructing a complex network of all defined disaster types, in order to finally intelligently extract the unique disaster chain of a specific disaster type. Google Scholar, Baidu Scholar and Sina News search engines are employed to acquire the needed data, and the respectively obtained disaster chains are compared with each other to show the robustness of our proposed approach. The achieved disaster chains are also compared with the ones concluded from existing research methods, and the very reasonable result is demonstrated. There is a great potential to apply this novel method in disaster management domain to find more secrets about disasters.