A Bibliometric Perspective on the Relationship Between Artificial Intelligence and Digital Culture
Article Sidebar
Main Article Content
Abstract
This study presents a bibliometric analysis of global research at the intersection of artificial intelligence and digital culture (2015–2025). It draws on 489 Scopus-indexed studies and follows the PRISMA framework. Findings show substantial growth during (2021–2024), with the United States leading output and robust international collaboration networks. The analysis confirms the centrality of artificial intelligence and the emergence of interconnected themes, underscoring the field’s interdisciplinary nature and the need for greater attention to its ethical, educational, and cultural dimensions.
Metrics
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Alkhammash, r. (2023). bibliometric, network, and thematic mapping analyses of metaphor and discourse in covid-19 publications from 2020 to 2022. frontiers in psychology, 13, 1062943 concrete published between 1974 and 2021. sustainability, 14(18), 11646.
Aria, m., & cuccurullo, c. (2017). bibliometrix: an r-tool for comprehensive science mapping analysis. journal of informetrics, 11(4), 959-975.
Atenstaedt, r. (2017). word cloud analysis of the bjgp: 5 years on. british journal of general practice, 67(658), 231-232.
Grant, M. J., &. (2009). A typology of reviews: an analysis of 14 review types and associated methodologies. ,. Health Information & Libraries Journal, 26(2), 91-108.
Lutfi, A. M.-O. ( 2021). Digital financial inclusion sustainability in Jordanian context. Sustainability (Switzerland). Sustainability (Switzerland, 13(11):6312. doi: https://doi.org/10.3390/su13116312
Idrissi Mokhtar.Abrou Djebli, Souar Youcef. «The importance of integrating fuzzy logic analysis and artificial intelligence in decision-making in economic organizations: ABibliometric Study.» المجلة الدولية للاداء الاقتصادي, 2024: 135.
Moro, S. G. (2019). A text mining and topic modelling perspective of ethnic marketing research. Journal of Business Research, 275-285.
Mustak, M. J. (2021). Artificial intelligence in marketing: Topic modeling, scientometric analysis, and research agenda. Journal of Business Research, 389-404.
Vanhala, M. L. (2020). The usage of large data sets in online consumer behaviour: A bibliometric and computational text-mining–driven analysis of previous research. journa of businnes rusearch, 46-59.
Xu, Y. S. (2021). An evolutionary perspective on the dynamics of service plat form ecosystems for the sharing economy. Journal of Business Research, 135: 127–136.
Castells, M. (2015). The Rise of the Network Society.
Ionescu, Ș., Delcea, C., Chiriță, N., & Nica, I. (2024). Exploring the Use of Artificial Intelligence in Agent-Based Modeling Applications: A Bibliometric Study. Algorithms, 17(1), 21.
jenkins, H. (2016). (2016). Participatory Culture in a Networked Era: A Conversation on Youth, Learning, Commerce, and Politics. Polity Press.
Russell, S. J., &. (2020). Artificial Intelligence: A Modern Approach (Vol. (4th ed.)). Pearson.
Sinkovics, N. (2016). Enhancing the foundations for theorising through bibliometric mapping. international marketing review, 33 (3): 327–350.
Van Eck, N. J., &. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics,, 84(2), 523-538.