A Hybrid LDA and Fuzzy CRITIC-MABAC Model for Smart City Ranking

A smart city is an urban development idea that seeks to efficiently incorporate diverse information and communication technology (ICT) solutions in a safe manner to properly oversee a city’s resources. The literature demonstrates an absence of a universally accepted and widely used definition. The essential criteria for assessing the development of smart cities and components is the prevailing paradigm in the context of smart cities are the focus of this research. The aforementioned inquiries constitute the aim of the proposed research. This study seeks to establish a complete evaluation framework that can adapt the variations in the concept of smart cities by incorporating advanced approaches, including latent-dirichlet-allocation (LDA), fuzzy criteria-importance-through-intercriteria-correlation (fuzzy CRITIC), and multi-attributive-border-approximation area comparison (MABAC), to assess and rank cities according to multi-dimensional criteria. Afterwards, the utilization of LDA, a technique for topic analysis, is employed to extract pertinent subjects and important insights. Subsequently, internet news pertaining to specific smart cities is methodically gathered and examined using LDA results, leading an enhanced objectivity. Next, the fuzzy CRITIC technique is utilized to calculate criteria weights. Weights are utilized in the MABAC method to rank the identified smart cities.