Trends and evolution of Scientometric and Bibliometric research in the SCOPUS database - SÃ¡nchez Castillo, Verenice; PÃ©rez Gamboa, Alfredo Javier; GÃ³mez Cano, Carlos Alberto (Bibliotecas. Anales de investigación, 2024)
Objective. The study focused on the in-depth and mixed exploration of the main trends of scientometric and bibliometric research in the SCOPUS database. Design/Methodology/Approach. A mixed, sequential, and integrative approach was used, divided into two stages. In the first, a bibliometric study was conducted to answer two fundamental questions. In the second qualitative procedures from integrative syntheses were developed and the main results were integrated. Results/Discussion. The results demonstrate the increase in studies developed from both disciplines, their growing collaborative and interdisciplinary nature, as well as the importance of continuing the development of their methodologies. The qualitative analysis allowed us to identify two fundamental themes in which the relationship between 11 categories, one of them shared, and 23 codes are configured. In general, the functions and potential offered by both types of studies are examined. Conclusions. The findings not only allowed us to characterize the main trends in bibliometric and scientometric studies, but also fundamental issues were discussed for a better understanding of these trends, specific recommendations were offered and various methodological aspects were assessed. It was concluded that there was a need to continue delving deeper into both disciplines, especially from the perspective of non-specialist users and the opening of future lines of research. Originality/Value. The research offers a solid and innovative methodology, consolidating a system of protocols implemented by transcendental authors and those generated by the academic networks to which the authors belong. Additionally, an expanded as well as in-depth review is offered, with a consistent foundation and qualitative analytical procedures for a better understanding of the data collected