ARTIFICIAL INTELLIGENCE IN QUALITATIVE RESEARCH: BIBLIOMETRIC ANALYSIS OF SCIENTIFIC PRODUCTION INDEXED IN SCOPUS
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Data de Publicação: | 2024 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | spa |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | https://doi.org/10.36367/ntqr.20.4.2024.e1116 |
Resumo: | The use of Artificial Intelligence (AI) in research has shown a growing trend in recent years, gaining significant attention from the scientific community compared to other techniques and software for information analysis. Objective to conduct an analysis of the main trends in the use of AI in qualitative research to characterize how AI is being employed in such scientific production. Methods involved a bibliometric analysis of scientific articles indexed in Scopus, using the VosViewer tool, followed by a conventional analysis of data grouped by type, volume of articles, citations, and their respective dating. Results identified four clusters; the first one concentrates 161 occurrences and a score of 572 in its relationship strength. Meanwhile, the second cluster recorded 144 occurrences and a score of 1004 in its relationship strength. Clusters 3 and 4 present lower relationship strength scores. Cluster 1 stands out because it presents the highest number of occurrences linked to the use of AI as the methodology used in the analyzed research. Characterization shows that research oriented towards knowledge production (pure research) surpasses research with an innovation component, representing only one-third of the total. The citation volume of the former also exceeds that of the latter. Additionally, it was observed that the fields of Computer Science and Medicine are the most prominent in this topic. Conclusions AI applied to qualitative research constitutes an increasingly common tool. Three key factors stand out in the use of AI in qualitative research: as a strategy to automate decision-making, to enhance human action, and to investigate as an effect of external factors. |
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ARTIFICIAL INTELLIGENCE IN QUALITATIVE RESEARCH: BIBLIOMETRIC ANALYSIS OF SCIENTIFIC PRODUCTION INDEXED IN SCOPUSEl INTELIGENCIA ARTIFICIAL EN LA INVESTIGACIÓN CUALITATIVA: ANÁLISIS BIBLIOMÉTRICO DE LA PRODUCCIÓN CIENTÍFICA INDIZADA EN SCOPUSBibliometric Analysis, Artificial Intelligence, Qualitative Research, ScopusThe use of Artificial Intelligence (AI) in research has shown a growing trend in recent years, gaining significant attention from the scientific community compared to other techniques and software for information analysis. Objective to conduct an analysis of the main trends in the use of AI in qualitative research to characterize how AI is being employed in such scientific production. Methods involved a bibliometric analysis of scientific articles indexed in Scopus, using the VosViewer tool, followed by a conventional analysis of data grouped by type, volume of articles, citations, and their respective dating. Results identified four clusters; the first one concentrates 161 occurrences and a score of 572 in its relationship strength. Meanwhile, the second cluster recorded 144 occurrences and a score of 1004 in its relationship strength. Clusters 3 and 4 present lower relationship strength scores. Cluster 1 stands out because it presents the highest number of occurrences linked to the use of AI as the methodology used in the analyzed research. Characterization shows that research oriented towards knowledge production (pure research) surpasses research with an innovation component, representing only one-third of the total. The citation volume of the former also exceeds that of the latter. Additionally, it was observed that the fields of Computer Science and Medicine are the most prominent in this topic. Conclusions AI applied to qualitative research constitutes an increasingly common tool. Three key factors stand out in the use of AI in qualitative research: as a strategy to automate decision-making, to enhance human action, and to investigate as an effect of external factors.El uso de la Inteligencia Artificial (IA) en la investigación ha mostrado una tendencia creciente en los últimos años, ganando un espacio importante en el interés de la comunidad científica, frente a otras técnicas y softwares de análisis de información. Mediante este trabajo, se pretende realizar un análisis de las principales tendencias en el uso de la IA en la investigación cualitativa que permita caracterizar de qué forma se está empleando la IA en dicha producción científica. Se empleó un análisis bibliométrico de artículos científicos, indizados en Scopus, mediante el uso de la herramienta VosViewer; y, posteriormente, se realizó un análisis convencional de datos agrupados por tipo, volumen de artículos y citas, así como su respectiva datación. Se identificaron cuatro clústeres: el primero agrupa 161 ocurrencias y una puntuación de 572 en su fuerza de relación. Por su parte, el segundo clúster registra 144 ocurrencias y una puntuación de 1004 en su fuerza de relación. Los clústeres 3 y 4 presentan puntuaciones inferiores de fuerza de relación. Se destaca el clúster 1 porque presenta la mayor cantidad de ocurrencias vinculadas al uso de IA como metodología utilizada en las investigaciones analizadas. La caracterización demuestra que las investigaciones orientadas a la producción de conocimiento (investigación pura) superan a las investigaciones con componente de innovación, que solo representan un tercio del total. El volumen de citación de las primeras también supera al de las segundas. Además, se observó que los campos de mayor auge en este tema son las Ciencias de la Computación y la Medicina. La IA aplicada a investigación cualitativa constituye una herramienta cada vez más frecuente. Sobresalen tres factores clave en el uso de IA en investigaciones cualitativas: como estrategia para automatizar la toma de decisiones, para potenciar la acción humana y para investigar como efecto de factores externos.Ludomedia2024-11-25info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://doi.org/10.36367/ntqr.20.4.2024.e1116https://doi.org/10.36367/ntqr.20.4.2024.e1116New Trends in Qualitative Research; Vol. 20 No. 4 (2024): New Trends in Qualitative Research; e1116New Trends in Qualitative Research; Vol. 20 Núm. 4 (2024): New Trends in Qualitative Research; e1116New Trends in Qualitative Research; Vol. 20 N.º 4 (2024): New Trends in Qualitative Research; e11162184-7770reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAPspahttps://publi.ludomedia.org/index.php/ntqr/article/view/1116https://publi.ludomedia.org/index.php/ntqr/article/view/1116/1063Copyright (c) 2024 New Trends in Qualitative Researchinfo:eu-repo/semantics/openAccessReyes Flores, Luis GerardoMejía Rivera, Kevin Arnaldo2024-12-01T10:10:51Zoai:ojs.publi.ludomedia.org:article/1116Portal AgregadorONGhttps://www.rcaap.pt/oai/openairemluisa.alvim@gmail.comopendoar:71602024-12-01T10:10:51Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
ARTIFICIAL INTELLIGENCE IN QUALITATIVE RESEARCH: BIBLIOMETRIC ANALYSIS OF SCIENTIFIC PRODUCTION INDEXED IN SCOPUS El INTELIGENCIA ARTIFICIAL EN LA INVESTIGACIÓN CUALITATIVA: ANÁLISIS BIBLIOMÉTRICO DE LA PRODUCCIÓN CIENTÍFICA INDIZADA EN SCOPUS |
title |
ARTIFICIAL INTELLIGENCE IN QUALITATIVE RESEARCH: BIBLIOMETRIC ANALYSIS OF SCIENTIFIC PRODUCTION INDEXED IN SCOPUS |
spellingShingle |
ARTIFICIAL INTELLIGENCE IN QUALITATIVE RESEARCH: BIBLIOMETRIC ANALYSIS OF SCIENTIFIC PRODUCTION INDEXED IN SCOPUS Reyes Flores, Luis Gerardo Bibliometric Analysis, Artificial Intelligence, Qualitative Research, Scopus |
title_short |
ARTIFICIAL INTELLIGENCE IN QUALITATIVE RESEARCH: BIBLIOMETRIC ANALYSIS OF SCIENTIFIC PRODUCTION INDEXED IN SCOPUS |
title_full |
ARTIFICIAL INTELLIGENCE IN QUALITATIVE RESEARCH: BIBLIOMETRIC ANALYSIS OF SCIENTIFIC PRODUCTION INDEXED IN SCOPUS |
title_fullStr |
ARTIFICIAL INTELLIGENCE IN QUALITATIVE RESEARCH: BIBLIOMETRIC ANALYSIS OF SCIENTIFIC PRODUCTION INDEXED IN SCOPUS |
title_full_unstemmed |
ARTIFICIAL INTELLIGENCE IN QUALITATIVE RESEARCH: BIBLIOMETRIC ANALYSIS OF SCIENTIFIC PRODUCTION INDEXED IN SCOPUS |
title_sort |
ARTIFICIAL INTELLIGENCE IN QUALITATIVE RESEARCH: BIBLIOMETRIC ANALYSIS OF SCIENTIFIC PRODUCTION INDEXED IN SCOPUS |
author |
Reyes Flores, Luis Gerardo |
author_facet |
Reyes Flores, Luis Gerardo Mejía Rivera, Kevin Arnaldo |
author_role |
author |
author2 |
Mejía Rivera, Kevin Arnaldo |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Reyes Flores, Luis Gerardo Mejía Rivera, Kevin Arnaldo |
dc.subject.por.fl_str_mv |
Bibliometric Analysis, Artificial Intelligence, Qualitative Research, Scopus |
topic |
Bibliometric Analysis, Artificial Intelligence, Qualitative Research, Scopus |
description |
The use of Artificial Intelligence (AI) in research has shown a growing trend in recent years, gaining significant attention from the scientific community compared to other techniques and software for information analysis. Objective to conduct an analysis of the main trends in the use of AI in qualitative research to characterize how AI is being employed in such scientific production. Methods involved a bibliometric analysis of scientific articles indexed in Scopus, using the VosViewer tool, followed by a conventional analysis of data grouped by type, volume of articles, citations, and their respective dating. Results identified four clusters; the first one concentrates 161 occurrences and a score of 572 in its relationship strength. Meanwhile, the second cluster recorded 144 occurrences and a score of 1004 in its relationship strength. Clusters 3 and 4 present lower relationship strength scores. Cluster 1 stands out because it presents the highest number of occurrences linked to the use of AI as the methodology used in the analyzed research. Characterization shows that research oriented towards knowledge production (pure research) surpasses research with an innovation component, representing only one-third of the total. The citation volume of the former also exceeds that of the latter. Additionally, it was observed that the fields of Computer Science and Medicine are the most prominent in this topic. Conclusions AI applied to qualitative research constitutes an increasingly common tool. Three key factors stand out in the use of AI in qualitative research: as a strategy to automate decision-making, to enhance human action, and to investigate as an effect of external factors. |
publishDate |
2024 |
dc.date.none.fl_str_mv |
2024-11-25 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://doi.org/10.36367/ntqr.20.4.2024.e1116 https://doi.org/10.36367/ntqr.20.4.2024.e1116 |
url |
https://doi.org/10.36367/ntqr.20.4.2024.e1116 |
dc.language.iso.fl_str_mv |
spa |
language |
spa |
dc.relation.none.fl_str_mv |
https://publi.ludomedia.org/index.php/ntqr/article/view/1116 https://publi.ludomedia.org/index.php/ntqr/article/view/1116/1063 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2024 New Trends in Qualitative Research info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2024 New Trends in Qualitative Research |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Ludomedia |
publisher.none.fl_str_mv |
Ludomedia |
dc.source.none.fl_str_mv |
New Trends in Qualitative Research; Vol. 20 No. 4 (2024): New Trends in Qualitative Research; e1116 New Trends in Qualitative Research; Vol. 20 Núm. 4 (2024): New Trends in Qualitative Research; e1116 New Trends in Qualitative Research; Vol. 20 N.º 4 (2024): New Trends in Qualitative Research; e1116 2184-7770 reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
mluisa.alvim@gmail.com |
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1817549884347121664 |