| Abstract |
A smart city is regarded as a new form of urban development proposed by humans to cope with urban problems. Smart cities are of great interest to theoretical circles and are favored by city governments. However, in China, research on common problems and solution strategies in the process of smart city construction is still insufficient. To address this insufficiency, we utilized Python language and the Selenium library to realize a web crawler and construct a smart city corpus background library. Then, the word2vec model was used for word vectorization to divide policy texts into phrases, and 132 policies from 85 cities above the prefecture level in China were analyzed using the Gaussian mixture model (GMM). The results showed many problems in the smart city construction process in China, including the homogenization of content, the wide topic coverage, the influence of higher-level governments, the mismatch with the local situation, and the neglect of relationship governance. Moreover, an efficiency-governance model was designed, and it held certain theoretical and practical guiding significance for further promoting the healthy and sustainable development of smart city construction in China. |
