Improvement Strategies of Urban Green Development Satisfaction Based on Text Analysis and SVM Algorithm

In this paper, we used the SVM algorithm and text analysis to study the views, feelings, and satisfaction of Xiamen citizens on the green development of Xiamen. Through the SVM algorithm, we classify the participants in the questionnaire on green development satisfaction and divide them into three groups, and then summarize the features of the classified groups. We also used text analysis to carry out the public complaint text crawled from the consultation and complaint module of the Xiamen Ecological Environment Bureau, and then the word frequency statistics and semantic network analysis of the complaint text were established. According to these pieces of information, we formulate strategies to improve the satisfaction of urban green development.