Journey of Urban Concepts: Mapping 30-Years of Shifts in the Meanings of Key Topics in Journal of American Planning Association,Journal of Planning Education and Research,and Journal of Planning Literature

Abstract

We examine topics’ interactions and changes of contexts in all publications in three general U.S.-based planning journals from 1992 to 2021. We do so using Bidirectional Encoder Representations from Transformers (BERT), a deep learning language model. We find 12 interrelated research topics. Moreover, the meaning and focal points of those topics have shifted over time. These shifts reflect evolving societal priorities, with long-standing themes such as urban form, economic development, and resilience increasingly intersecting with concerns around equity, governance, and sustainability. The results offer insights to empower cross-domain collaboration and adaptive responses to emerging urban challenges.

Keywords

planning journals semantic analysis topic modeling deep learning large language modeling

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