Planning interventions have been applied to improve the well‐being, hereafter happiness, of residents. The happiness in shrinking cities, in particular, becomes more critical since urban decline tends to induce an unequal and uneven distribution of care under a limited budget and human resources. Using geo‐tagged Twitter, census, and geospatial data on Detroit, Michigan, which is one of the well‐known shrinking cities in the U.S., the spatial distribution of sentiments, topics of tweets appeared, and the association between neighborhood conditions and the level of happiness were examined. The outcomes indicate that people in Detroit are posting happy tweets more than negative tweets. The downtown area holds both positive and negative hotspots, which are clustered around sports arenas and bars, respectively. Neighborhoods with young and well‐educated residents, situated close to amenities (i.e., recreation facilities, colleges, and commercial areas), and less crime tend to be happier. The use of SNS data could serve as a meaningful social listening tool to reconcile the declining urban vitality of neighborhoods since people interact with those spaces. Negative sentiments are attached to specific neighborhoods with certain conditions so that regeneration efforts should take place in neighborhoods with a higher priority.

中文翻译：

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快乐的社区：使用Twitter数据调查不断缩小的城市的社区条件和情绪

规划干预措施已用于改善居民的幸福感（此后称为幸福感）。特别是在萎缩的城市中，幸福感变得尤为重要，因为在预算和人力资源有限的情况下，城市的衰落往往会导致护理分配不均和分布不均。使用美国密西根州底特律市（美国最著名的缩小城市之一）上带有地理标签的Twitter，人口普查和地理空间数据，情感的空间分布，推文主题以及邻里条件和水平之间的关联出现了的幸福感得到了检验。结果表明，底特律的人们发布的快乐推文多于负面的推文。市中心地区既有积极热点，也有消极热点，分别集中在运动场和酒吧周围。居民附近有年轻且受过良好教育的社区，靠近便利设施（即娱乐设施，大学和商业区），犯罪率较低，往往更幸福。SNS数据的使用可以作为一种有意义的社交倾听工具，以调和社区与社区之间不断下降的城市活力，因为人们正在与这些空间互动。负面情绪依附于具有特定条件的特定社区，因此应在具有较高优先级的社区中进行再生工作。