Trends and Networks in the Application of MCDM Methods in Computer Science

This paper presents a comprehensive bibliometric analysis of scientific output in the field of Multi-Criteria Decision-Making (MCDM) within the context of computer science, focusing on the period from 2019 to mid-2025. Using data from the Web of Science Core Collection, a total of 302 relevant papers were identified based on criteria such as publication year, language, document type, open access status, and research area. The analysis covers publication dynamics, the most influential authors and institutions, thematic directions, and collaboration structures. Special emphasis is placed on citation analysis of the most impactful works, as well as the visualization of co-authorship networks using the PRISMA methodology and tools such as RStudio and Biblioshiny. The results reveal a growing trend in publications, high activity by certain authors (e.g., Akram M and Liu Y), and strong collaboration within research clusters. Dominant topics include decision-making models, alternative selection, aggregation operators, and priority evaluation. This study provides insights into the structure and dynamics of the scientific community engaged in MCDM methods in computer science and may serve as a guide for future researchers, practitioners, and scientific development strategies.