基于文本挖掘的城市环境治理智能化能力评估方法及案例应用

Assessment Method and Case Application of Urban Environmental Governance Intelligence Capability Based on Text Mining

中文关键词:  环境治理智能化  技术创新能力  应用落地能力  自然语言处理

英文关键词:intelligent environmental governance  technological innovation capability  application implementation capability  natural language processing

中文摘要:

      新兴数字技术的快速发展推动了环境治理的智能化转型，但各城市环境治理智能化能力差异较大。本研究从技术创新和应用落地两个环节建立分析框架，选取10个案例城市2014—2023年为研究对象，基于海量专利、政策文本等数据评估不同智能技术类型和环境治理目标下案例城市环境治理智能化能力水平。研究结果表明：①研究期内案例城市的技术创新能力与应用落地能力均显著提升，分别上升633%和559%，其中北京、上海保持领先。②各城市发展侧重不同，上海注重应用落地而南京强化技术创新；合肥、南京以人工智能为主导，武汉优先建设大数据基础；成都、上海、北京侧重项目实践，合肥、广州聚焦政策体系完善。③各城市智能技术类型呈现“重硬轻软”的失衡；环境治理目标呈现从“技术创新专业化突破”向“应用落地均衡化发展”的演进规律。④从城市发展路径上看，技术创新易受政策、经济等短期因素影响而波动，应用落地则呈现渐进累积特征。研究建议加强大数据与人工智能深度融合，平衡软硬件协调发展，健全政策落地执行机制，以提升环境治理智能化整体效能。

英文摘要:

      The rapid development of emerging digital technologies has driven the intelligent transformation of environmental governance, yet significant disparities exist in the environmental governance intelligence capabilities across cities. This study establishes an analytical framework from two dimensions—technological innovation and application implementation—and selects 10 case cities from 2014-2023 as research subjects. Based on massive patent and policy text data, the study evaluates the environmental governance intelligence capability levels of case cities across different intelligent technology types and environmental governance objectives. The findings indicate: ① Both technological innovation and application implementation capabilities of the case cities improved significantly during the study period, increasing by 633% and 559%, respectively, with Beijing and Shanghai maintaining leading positions. ② Development priorities varies among cities: Shanghai emphasizes application implementation while Nanjing strengthens technological innovation; Hefei and Nanjing are primarily driven by artificial intelligence, whereas Wuhan prioritizes big data infrastructure development; Chengdu, Shanghai, and Beijing focus on project-based practices, while Hefei and Guangzhou concentrate on policy framework refinement. ③ Cities exhibit an imbalanced pattern of “emphasizing hardware over software” in intelligent technology types, while environmental governance objectives show an evolutionary pattern from “specialized breakthroughs in technological innovation” to “balanced development in application implementation.” ④ In terms of urban development pathways, technological innovation is susceptible to short-term fluctuations influenced by policy and economic factors, while application implementation demonstrates progressive accumulative characteristics. It is recommended to deepen the integration of big data and artificial intelligence, balance the coordinated development of hardware and software, and improve the policy implementation mechanisms to enhance overall environmental governance intelligence effectiveness.