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                            [identifier] => oai:ojs2.ijsmc.pro-metrics.org:article/168
                            [datestamp] => 2025-01-03T20:46:10Z
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                                    [title] => Array
                                        (
                                            [0] => Artificial intelligence in finance studies: Bibliometric approach to literature indexed in Scopus
                                            [1] => La inteligencia artificial en los estudios de finanzas: aproximación bibliométrica a la literatura indizada en Scopus
                                        )

                                    [creator] => Array
                                        (
                                            [0] => Rodriguez, William Joel Marín
                                            [1] => Jordán, Flor de María Lioo
                                            [2] => Flores, Viviana Inés Vellón
                                            [3] => Armas, Timoteo Solano
                                            [4] => Girón, Elia Clorinda Andrade
                                        )

                                    [subject] => Array
                                        (
                                            [0] => finance
                                            [1] => artificial intelligence
                                            [2] => bibliometrics
                                            [3] => scientific production
                                            [4] => finanzas
                                            [5] => inteligencia artificial
                                            [6] => bibliometría
                                            [7] => producción científica
                                        )

                                    [description] => Array
                                        (
                                            [0] => Abstract 
Objective. This study aims to analyze the scientific production indexed in the Scopus database on the application of artificial intelligence (AI) to finance studies between 2007 and 2023.
Design/Methodology/Approach. The study design is non-experimental (transectional) and quantitative (descriptive). The most representative authors, the documentary typology that supports the results, and the principal publications were identified and analyzed. General citation indicators were calculated to ascertain the scientific impact associated with the topic. Spectral maps of country and word density were prepared to determine the main characteristics concerning these bibliographic variables.
Results/Discussion. Notwithstanding the extensive temporal scope of the study, the application of AI to finance has not been evidenced in the extant literature until 2017. No significant contributors or highly influential journals are identified; studies are sporadic and consistent with the topic's novelty. Nevertheless, this subject has a high scientific impact, with an average of 20 citations per paper.
Conclusions. The application of AI in finance is a relatively recent phenomenon. The countries of Asia and India are at the forefront of scientific production, as evidenced by Scopus's data analysis. The works analyzed exhibit a high density of terminology and a plethora of journals in the computational field that publish on this topic. Furthermore, publication practices manifest in the form of event papers, which are published at a similar rate to scientific articles.
Originality/Value. The value of this study lies in its originality, which stems from an in-depth examination of existing literature on these topics in Scopus. This approach enables a comprehensive bibliometric analysis, informing future research in this field.
                                            [1] => Objetivo. El objetivo del estudio es analizar la producción científica indizada en la base de datos de Scopus sobre inteligencia artificial (IA) aplicada a los estudios de finanzas entre los años 2007 y 2023.
Diseño/Metodología/Enfoque. El diseño del estudio es no experimental (transeccional) y cuantitativo (descriptivo). Se identificaron los autores más representativos, la tipología documental que soporta los resultados y las principales publicaciones. Se calcularon indicadores generales de citas para determinar el impacto científico asociado al tema. Se elaboraron mapas espectrales de densidad de países y palabras con el fin de identificar las principales características respecto a estas variables bibliográficas.
Resultados/Discusión. A pesar de que el estudio abarca un amplio marco temporal, los estudios de IA aplicados a las finanzas no aparecen en la literatura hasta el año 2017. No se identifican grandes productores ni revistas altamente representativas, sino que hay estudios que aparecen de manera ocasional, lo cual está relacionado con la novedad del tema. Sin embargo, se trata de una temática con un elevado impacto científico y, de media, se reciben 20 citas por documento.
Conclusiones. Los estudios sobre la aplicación de la IA en las finanzas son recientes. Asia e India lideran la producción científica analizada en Scopus. Existe una alta densidad de terminología asociada a los trabajos analizados, así como de revistas del campo computacional que publican sobre esta temática. Por otra parte, las prácticas de publicación aparecen en forma de ponencias de eventos, publicadas en una proporción similar a la de los artículos científicos.
Originalidad/Valor. La originalidad radica en estudiar la literatura sobre estos temas en Scopus y por tanto su valor radica en contar con un análisis bibliométrico sobre el tema para futuras investigaciones.
                                        )

                                    [publisher] => Pro-Metrics
                                    [date] => 2025-01-03
                                    [type] => Array
                                        (
                                            [0] => info:eu-repo/semantics/article
                                            [1] => info:eu-repo/semantics/publishedVersion
                                            [2] => Peer-reviewed article
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                                    [format] => Array
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                                            [0] => application/pdf
                                            [1] => application/pdf
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                                    [identifier] => Array
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                                            [0] => https://ijsmc.pro-metrics.org/index.php/i/article/view/168
                                            [1] => 10.47909/ijsmc.168
                                        )

                                    [source] => Array
                                        (
                                            [0] => Iberoamerican Journal of Science Measurement and Communication; Vol. 5 No. 1 (2025): In progress; 1-8
                                            [1] => 2709-3158
                                            [2] => 2709-7595
                                        )

                                    [language] => Array
                                        (
                                            [0] => spa
                                            [1] => eng
                                        )

                                    [relation] => Array
                                        (
                                            [0] => https://ijsmc.pro-metrics.org/index.php/i/article/view/168/114
                                            [1] => https://ijsmc.pro-metrics.org/index.php/i/article/view/168/115
                                        )

                                    [rights] => Array
                                        (
                                            [0] => Copyright (c) 2025 William Joel Marín Rodriguez, Flor de María Lioo Jordán, Viviana Inés Vellón Flores, Timoteo Solano Armas, Elia Clorinda Andrade Girón
                                            [1] => https://creativecommons.org/licenses/by-nc/4.0
                                        )

                                )

                        )

                )

        )

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