Examining the public’s attention and comments on smart city topics in social media can help enable a full understanding of the development characteristics of smart cities, and provide a realistic reference for improving the level of public participation and citizens’ sense of acquisition in smart city construction. Based on Sina Weibo, a well-known social media platform in China, over 230,000 public comments related to smart cities were extracted to analyze. Using LDA (Latent Dirichlet Assignment) and CNN-BiLSTM (Convolutional Neural Network and Bi-directional long and short memory) models, a topic mining and sentiment analysis model for user comments was constructed to study the current state of public perception of smart city concepts. The results demonstrate that public discussions on smart cities were macro-oriented, focusing on strategic layout and technical applications. As public awareness of smart cities deepens, topics about application scenarios and social services are gradually emphasized. The public’s positive sentiment toward smart cities dominates and varies in sentiment intensity across years; the positive sentiment intensity of individual users on smart city ideas is significantly lower than that of official certified Weibo users, such as government departments and corporate organizations, which reveals the identity and temporal characteristics of public participation in cyberspace.

Production efficiency is a critical research topic in the field of construction economics and management. It reflects the developmental potential and competitiveness of the economy or an economic system. An objective and reasonable assessment framework of the production efficiency in the construction industry is essential to promote the industry’s high-quality development. This study aims to propose a scientific and holistic framework to examine the production efficiency in the construction industry and to investigate evolution patterns from a macroeconomic perspective. Input and output indicators were identified through the value-added and the fuzzy Delphi methods. In addition, the production efficiency in the construction industry was examined via the bootstrap-DEA and Malmquist exponential decomposition models. A case study in China was conducted at the end of this research. The panel data of 31 provinces from 2010 to 2020 were applied in the case study. The results reveal the following: (1) The bootstrap-DEA model results show that the trends of production efficiency before and after rectification are similar, but the difference is largest at the peak. Moreover, the production efficiency value after correction is evidently lower than that which is obtained by the traditional DEA model. (2) The Malmquist index decomposition results show that the change trend of technical efficiency in the construction industry is contrary to that of the scale efficiency. In addition, the improvement of scale efficiency cannot bring a melioration of management efficiency or the accumulation of production experience. (3) There is no direct correlation between production efficiency and economic development. High-value areas and median areas are contiguous, and they are mainly distributed in the central and eastern provinces. The findings accurately reflect construction industry productivity, providing practical data for developing policy recommendations for bridging regional construction development gaps.

Understanding the layout of China’s fintech policy planning from the perspective of policy science theory will help policy makers to fully understand the current development stage and evolutionary path of fintech and improve the implementation of fintech policies and the promotion of their effects. This study examines 120 fintech policies issued at the national level from 2017 to 2022; unifies policy tools, policy organizational structure, and policy effectiveness into a three-dimensional scientific policy analysis framework; and uses a text content mining method to provide a quantitative analysis of China’s current fintech policy system. In terms of the choice of policy tools, there is an unbalanced proportion, with environmental-type policy tools being overused and demand-type policy tools being underused; a network of core institutions for policy promulgation has been formed, with diversified types of subjects. However, overall, the degree of cooperation among various subjects is not high, and some departments closely related to the development of fintech are not involved enough in the publication of cooperation documents. Policy effectiveness depends on the number of policies and their average effectiveness, and the latter has insufficient growth momentum. Given the existing problems, some suggestions are made for optimising policies to develop fintech.

China is undergoing rapid urbanization, which has caused undesirable urban sprawl and ecological deterioration. Combining information technology for ecological environment governance is an effective measure to improve governance efficiency. In this paper, based on the analysis of the ecological restoration and governance case of S Island in Chongqing, an ecological intelligent governance system architecture based on the integration of multiple information technologies such as digital twin is extracted. The research shows that the S Island is based on the technical concept of the digital twin, and integrates a variety of information technology integration, collects and processes a large amount of data generated in the whole process of S Island repair and operation, and builds it based on the digital twin concept and accurately maps the physical space. This system model can be stored and processed based on the integrated data, realize knowledge graph visualization, algorithm optimization, and iterative integration for different objects and application scenarios, and finally serve different functional modules in ecological governance, which can be used to support Smart governance of cities.

As China is the largest developing country and the country with the largest volume of smart city construction, the Chinese government has promulgated a series of policies to develop smart cities vigorously. Thus, the understanding of smart city policies from the perspective of policy science theory is helpful in achieving a full understanding of the development stage and evolution path of smart cities and improving the implementation of smart city policies. In this study, text content mining and quantitative empirical analysis are used to investigate the structure and function of China’s smart city policy. The results demonstrate that China’s smart city policy has largely realized the evolutionary process of the policy keynote from “taking” to “giving” and the policy subject from “single” to “pluralistic”. The organizational structure has gradually turned from “multidisciplinary” to “cooperative governance”. The analysis results indicate that the policy guidance for smart cities should focus on the positive interaction between social needs and urban development regulations. It is also important to enhance citizen participation and redefine the role of the government in the development of smart cities.