The benefits of the natural environment in urban space have been explored in numerous studies. However, only a few statistics and studies have been conducted on the correlation between emotion and urban waterfront space, especially considering gender differences. Taking Wuhan city as an example, this study puts forward a new approach and perspective. Text emotion analysis is combined with the spatial analysis technique based on big data of social media. Based on the emotions of the public of different genders in urban space, suggestions are provided for urban planning and development from the perspective of POI (Point of Interest). The main steps are: (1) Analyzing the emotional score of Weibo texts published by citizens in the waterfront area of 21 lakes in Wuhan City; (2) exploring the public emotion characteristics of different genders in the urban waterfront; (3) classifying the waterfront according to the emotional response (score) of the public of different genders; (4) exploring the relationship between different POI types and waterfront types and proposing planning suggestions. The results of this study provide evidence for gender differences and spatial distribution of public emotions in the Wuhan waterfront area. It can help decision-makers to judge the prior protection and development direction of waterfront space, thus demonstrating the feasibility of this approach.

中文翻译：

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基于社交媒体文本的性别差异探索武汉海滨微博用户情绪的空间分布特征

许多研究都探讨了自然环境在城市空间中的好处。但是，关于情感与城市滨水空间之间的相关性，只有很少的统计和研究，特别是考虑到性别差异。本研究以武汉市为例，提出了一种新的方法和观点。文本情感分析与基于社交媒体大数据的空间分析技术相结合。根据城市空间中不同性别的公众的情绪，从POI（兴趣点）的角度为城市规划和发展提供了建议。主要步骤如下：（1）分析武汉市21个湖滨水区居民发布的微博文本的情感评分；（2）探索城市滨水区不同性别的公众情感特征；（3）根据不同性别的市民的反应（得分）对滨水区进行分类；（4）探索不同兴趣点类型与滨水类型之间的关系，并提出规划建议。这项研究的结果为武汉海滨地区的性别差异和公众情绪的空间分布提供了证据。它可以帮助决策者判断滨水空间的优先保护和发展方向，从而证明这种方法的可行性。（4）探索不同兴趣点类型与滨水类型之间的关系，并提出规划建议。这项研究的结果为武汉海滨地区的性别差异和公众情绪的空间分布提供了证据。它可以帮助决策者判断滨水空间的优先保护和发展方向，从而证明这种方法的可行性。（4）探索不同兴趣点类型与滨水类型之间的关系，并提出规划建议。这项研究的结果为武汉海滨地区的性别差异和公众情绪的空间分布提供了证据。它可以帮助决策者判断滨水空间的优先保护和发展方向，从而证明这种方法的可行性。