This paper offers a comprehensive overview of academic research on sentiment analysis in urban built environments from 2000 to 2025. Based on data from the scientific database Scopus and drawing on bibliometric tools like Bibliometrix (R) and VOSviewer for performance analysis and scientific mapping, it identifies publication trends, key influential works, leading authors and institutions, funding sources, and thematic clusters. The final dataset comprises 1315 English-language documents authored by 3855 researchers across 160 sources, with a total of 14,058 citations worldwide. The academic production increased after 2009, peaking in 2025. Keyword and network analyses highlight central themes (and methodological approaches) to the study of sentiment analysis in urban built environments. These include social media platforms like Twitter/X, machine learning, smart cities, artificial intelligence, mental health, and urban planning. China, the USA, and India lead in publication output. Over the last twenty-five years, key publication outlets included Sustainability (Switzerland), Cities, and the International Journal of Environmental Research and Public Health, while the National Natural Science Foundation of China has been the main funder. The paper discusses how sentiment analysis can support urban planning and public health by linking environmental features to well-being and explores emerging methodological trends like deep learning, multimodal approaches, and context-aware models. Overall, it maps the field’s intellectual landscape and argues in future directions for human-centered, data-driven urban decision-making.