Research on Information Channel of Climate Change Risk Perception of Shaanxi People

• Published in: Journal of risk analysis and crisis response 2021-04, Vol.11 (1), p.36-44
• Main Authors: Xue, Si Wen, Zhou, Qi
• Format: Article
• Language: English
• Subjects: ANN neural network model; CART decision tree model; information channel of climate change risk perception; Research Article; Shaanxi Province
• ISSN: 2210-8491; 2210-8505; 2210-8505
• DOI: 10.2991/jracr.k.210331.001

We take Shaanxi Province as the research area, aiming at exploring the information channel or path of climate change risk perception of Shaanxi people. It is desirable for us to carry out information channel or path classification of climate change risk perception based on survey data involving 5493 people in Shaanxi Province. Firstly, we use a Back Propagation (BP) neural network method to fit the information path of climate change risk perception. Secondly, a decision tree model is adopted to classify information channels of climate change risk perception. The results show that 300 neurons are needed in the information channel of climate change risk perception of Shaanxi people. The first path which influences climate change risk perception of Shaanxi people is as follows: indirect perception—direct perception—indirect perception—conductive perception. The second path is indirect perception—conductive perception. The third path is as below: indirect perception—direct perception—conductive perception, which also impacts climate change risk perception. According to varying information channels or paths of climate change risk perception, the public can formulate different risk management strategies to improve the level of climate change risk perception.