Assessment of city sustainability from the perspective of multi-source data-driven

From the perspective of multi-source data-driven, this paper combined the traditional assessment data with the network data, that is, integrating the behavioral guidance ideas and the emotional needs of the public in the assessment process. Through the emotional analysis of the network data, the subjective weight of the social, economic, and environmental systems were determined. This method not only reduces the cost of group decision making but also improves the assessment effect. At the same time, the objective weight with behavioral guidance was obtained by dynamic data analysis of the traditional assessment data. The sustainability performances of 14 cities in Liaoning, China were investigated. The results indicate that the sustainability was not ideal, most cities showed a downward trend. In addition, this paper concluded that the public in Liaoning paid the highest attention to the environmental system, followed by economic system and social system. Through curve fitting regression of the results, it is seen that in at this stage, it is not that the greater the indicator improvement of one system, the better the development of the other systems. It is suggested to make overall plans for the development of the three systems in light of the actual situation.

Automated summary

This paper integrates traditional assessment data with network data, combining behavioral guidance ideas and public emotional needs to determine the weight of different systems and improve the evaluation effect. The study found that the sustainability performances of 14 cities in Liaoning, China need improvement, with the public showing the highest attention to the environmental system and a downward trend in overall sustainability.