Título: Computational experiments in Computer Science: A bibliometric study

Autor(es): GUEVARA VEGA CATHY PAMELA, LANDETA LOPEZ PABLO ANDRES

Fecha de publicación: 13-feb-2025

Resumen: Introduction: Computational Experiments are crucial in various fields, including biological sciences, engineering, social sciences, etc., and are a powerful tool for understanding complex systems, optimizing processes, and driving innovation. Their importance lies in their ability to integrate with experimental methods, facilitate simulation-based learning, and provide cost-effective, scalable, and flexible solutions for analyzing complex systems. The purpose of this study is to make a bibliometric analysis of the research related to Computational Experiments in Computer Science. Methods: This bibliometric analysis was performed using information from 2013 and 2024 from the Scopus and Web of Science databases, with published articles This bibliometric study followed the guidelines proposed in the publication “How to conduct a bibliometric analysis: An overview and guidelines” by the author Gonthu N. To answer the research questions, the number of articles per year, number of articles per country, number of articles per subject area, list of main journals, and citation analysis were analyzed. Results: The results show that Scopus has more publications on the subject, China is the country that publishes more on the subject, Mathematics is the predominant subject area, finally, a co-occurrence analysis was performed where a total of 27 clusters were found in Scopus and 10 clusters in WoS. From this, the 10 most relevant keywords in each of the databases were identified. Conclusions: This review can be a basis in order that researchers to have a starting point for the current state of publications on Computational Experiments for future research.

Palabras clave: Computational Experiment; Computer Science; Operations Research; Optimization; Bibliometric Analysis.

DOI: https://doi.org/10.56294/dm2025188

ISSN: 2953-4917

Tipo publicación: Artículo