Natural Language Processing in Urban Planning: A Research Agenda

Abstract

The urban planning profession is increasingly challenged to analyze extensive text data, from plans to public feedback. While natural language processing (NLP) has promising potential for aiding this analysis, its applications and purpose in planning remain unclear. This article reviews current planning research using NLP, seeking to highlight key themes and challenges, and suggesting a coherent future research agenda. The results reveal that existing research is primarily exploratory with a fragmented research landscape. Future studies should focus on sharing data, benchmarking NLP techniques, fostering collaborative research tailored to planning, and addressing ethical implications to harness NLP's full potential in planning.