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This paper offers a comprehensive overview of academic research on sentiment analysis in urban built environments from 1999 to 2024. 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 871 English‐language documents authored by 2,068 researchers across 307 sources in 70 countries, with a total of 5,642 citations worldwide. The academic production increased after 2009, peaking in 2024. 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/X, machine learning, Natural Language Processing, smart cities, and tourism. China, the USA, and India lead in publication output. Over the last twenty-five years, key publication outlets include the International Journal of Environmental Research and Public Health, Cities, and Lecture Notes in Computer Science, while the National Natural Science Foundation of China is the most common funder. The paper discusses how sentiment analysis can support urban planning and public health by linking environmental features to well-being and explores methodological emerging trends like deep learning, multimodal approaches, and context-aware models. Overall, it maps the intellectual landscape of the field and argues for future directions for human-centred, data-driven urban decision-making.