Before revision:  This paper aims to fill this gap by focusing on investigating public attitudes towards disaster response and analyzing targeted relief supplies during disaster relief. The research comprises four steps. First, this paper implements Python in grasping Twitter data, and then, we assess public perceptron quantitatively by these opinioned texts ,  which contain information like the demand for targeted relief supplies, satisfactions of disaster response and fear of the public .
After revision:  This paper aims to fill this gap by focusing on investigating public attitudes towards disaster response and analyzing targeted relief supplies during different types of disasters. We focus on different natural disasters based on properties such as types, durations, and damages, which contains a total of 41 , which contain information like the demand for targeted relief supplies, satisfactions of disaster response and fear of the public .