Smart cities, as a novel concept in the organization and management of urban spaces, have increasingly attracted attention in urban studies in recent years. The expansion of digital technologies, the growth of big data, and the increasing complexity of urban challenges have positioned the smart city concept as a central theme in urban planning and management research. Despite the rapid growth of this field, its thematic dispersion and conceptual diversity have made it difficult to clearly understand the knowledge structure, evolutionary trajectories, and major research directions within the domain. In this context, systematic analysis of the scientific literature can help clarify the dimensions of this field and identify major research trends.

This study aims to map the scientific landscape and analyze the knowledge structure of smart city research using a bibliometric approach. The dataset consists of 1,040 scientific publications indexed in the Scopus database between 2003 and 2026. Within this framework, the temporal distribution of publications, keyword co-occurrence patterns, thematic clusters, and emerging research trends were analyzed to provide a comprehensive picture of the conceptual structure and developmental trajectory of this field.

The findings indicate that scientific production in this domain has grown rapidly, particularly since 2015. The conceptual structure of smart city studies is mainly organized into clusters related to data-driven infrastructures, smart technologies, urban service systems, and security and privacy issues. Trend analysis also reveals a shift toward advanced topics such as digital twins, edge computing, blockchain, and cybersecurity, highlighting emerging directions for future research and urban governance.