The Application of Artificial Intelligence in Participatory Urban Planning: Emphasizing Natural Language Processing (NLP)

Participatory urban planning aims to increase citizen involvement in urban decision-making and requires tools for analyzing vast amounts of textual data. This study investigates the application of Natural Language Processing (NLP) in analyzing citizens' opinions regarding urban development plans.

Using content analysis methods and machine learning algorithms, opinions collected from social media platforms were analyzed. The results indicated that NLP can accurately identify sentiments, main topics, and patterns present in citizens' comments.

These findings suggest that NLP can serve as a powerful tool to enhance the decision-making process in urban planning. However, limitations such as informal language and the presence of specialized terminology in comments indicate a need for further development of NLP models.