Immersive childhoods and algorithmic communication: a bibliometric analysis of identity and misinformation in generative metaverses (2010-2025)
Article Sidebar
Main Article Content
Abstract
Introduction: This study explores how immersive childhoods shape emerging forms of identity, learning, and exposure to misinformation within generative metaverses between 2010 and 2025. Methodology: Using an exploratory-descriptive bibliometric approach, a systematic review was conducted under PRISMA-S guidelines, drawing data from Scopus and Web of Science and processed through Bibliometrix and Biblioshiny in R. Results: The final corpus of 383 documents and 216 sources enabled mapping of productivity, collaboration, and conceptual co-occurrence patterns related to algorithmic communication and artificial intelligence in digital childhood research. Discussion: Findings reveal steady scientific growth, four major thematic clusters—algorithmic infrastructure, immersive learning, machine-learning optimization, and semantic communication—and above-average international collaboration within the social sciences. Ethical and educational gaps emerge in child representation and data governance, indicating an early stage of interdisciplinary maturity. Conclusions: Research on generative metaverses and digital childhoods demands explainable analytical frameworks, algorithmic literacy, and child-protection strategies grounded in equity, transparency, and responsible design.
Downloads
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
The Journal of Communication of SEECI recognizes and promotes copyright rights, as well as the need to disseminate knowledge in an accessible and equitable manner. Our journal operates under a Creative Commons License CC BY-NC 4.0, which allows authors and users to:
- Share and Adapt: Copy, redistribute, and adapt the material published in the journal in any medium or format.
- Attribution: Properly acknowledge authorship and provide a link to the license, indicating if any changes have been made.
- Non-Commercial: Do not use the material for commercial purposes without the express permission of the authors and the journal.
- Authors retain copyright and may enter into non-exclusive agreements for self-archiving, deposit, or distribution of the publisher's version published in this journal, including institutional, national, or international repositories, and personal websites.
References
Almarzouqi, A., Aburayya, A., y Salloum, S. A. (2022). Prediction of users’ intention to use metaverse system in medical education: A hybrid SEM-ML learning approach. IEEE Access, 10, 43421-43434. https://doi.org/10.1109/ACCESS.2022.3169285
Aria, M., y Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959-975. https://doi.org/10.1016/j.joi.2017.08.007
Bornmann, L., y Mutz, R. (2015). Growth rates of modern science: A bibliometric analysis based on the number of publications and cited references. Journal of the Association for Information Science and Technology, 66(11), 2215-2222. https://doi.org/10.1002/asi.23329
Bradford, S. C. (1934). Sources of information on specific subjects. Engineering, 137, 85-86. https://doi.org/10.1177/016555158501000407
Callon, M., Courtial, J.-P., y Laville, F. (1991). Co-word analysis as a tool for describing the network of interactions between basic and technological research. Scientometrics, 22(1), 155-205. https://doi.org/10.1007/BF02019280
Cobo, M. J., López-Herrera, A. G., Herrera-Viedma, E., y Herrera, F. (2011). Science mapping software tools: Review, analysis, and cooperative study among tools. Journal of the American Society for Information Science and Technology, 62(7), 1382-1402. https://doi.org/10.1002/asi.21525
Damaševičius, R., y Sidekerskienė, T. (2024). Virtual worlds for learning in the metaverse: A narrative review. Sustainability, 16(5), 2032. https://doi.org/10.3390/su16052032
Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., y Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285-296. https://doi.org/10.1016/j.jbusres.2021.04.070
Fortunato, S., Bergstrom, C. T., Börner, K., Evans, J. A., Helbing, D., Milojević, S., Petersen, A. M., Radicchi, F., Sinatra, R., Uzzi, B., Vespignani, A., Waltman, L., Wang, D., y Barabási, A.-L. (2018). Science of science. Science, 359(6379), eaao0185. https://doi.org/10.1126/science.aao0185
Garlinska, M., Osial, M., Proniewska, K., y Pregowska, A. (2023). The influence of emerging technologies on distance education. Electronics, 12(7), 1550. https://doi.org/10.3390/electronics12071550
Ilić, M. P., Păun, D., Popović Šević, N., Hadžić, A., y Jianu, A. (2021). Needs and performance analysis for changes in higher education and implementation of artificial intelligence, machine learning, and extended reality. Education Sciences, 11(10), 568. https://doi.org/10.3390/educsci11100568
Khan, L. U., Saad, W., Niyato, D., Han, Z., y Hong, C. S. (2022). Digital-twin-enabled 6G: Vision, architectural trends, and future directions. IEEE Communications Magazine, 60(1), 74-80. https://doi.org/10.1109/MCOM.001.21143
Lotka, A. J. (1926). The frequency distribution of scientific productivity. Journal of the Washington Academy of Sciences, 16(12), 317-323. https://www.jstor.org/stable/24529203?seq=1
Nalbant, K. G., y Aydın, S. (2023). Development and transformation in digital marketing and branding in the metaverse universe. Journal of Metaverse, 3(1), 9-18. https://doi.org/10.57019/jmv.1148015
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., … Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, n71. https://doi.org/10.1136/bmj.n71
Park, S.-M., y Kim, Y.-G. (2022). A metaverse: Taxonomy, components, applications, and open challenges. IEEE Access, 10, 4209-4251. https://doi.org/10.1109/ACCESS.2021.3140175
Pope, A. (1975). Bradford’s law and the periodical literature of information science. Journal of the American Society for Information Science, 26(4), 197-204. https://doi.org/10.1002/asi.4630260403
Rethlefsen, M. L., Kirtley, S., Waffenschmidt, S., Ayala, A. P., Moher, D., Page, M. J., y Koffel, J. B. (2021). PRISMA-S: An extension to the PRISMA statement for reporting literature searches in systematic reviews. Journal of the Medical Library Association, 109(3), 395-406. https://doi.org/10.5195/jmla.2021.962
Rogers, E. M. (2003). Diffusion of innovations (5th ed.). Free Press. https://books.google.es/books?id=9U1K5LjUOwEC&printsec=frontcover&redir_esc=y#v=onepage&q&f=false
Tewari, A., Fried, O., Thies, J., Sitzmann, V., Lombardi, S., Sunkavalli, K., Martin-Brualla, R., Simon, T., Niessner, M., Pandey, R., Fanello, S., Wetzstein, G., Zhu, J.-Y., Theobalt, C., Agrawala, M., Shechtman, E., Goldman, D. B., y Zollhöfer, M. (2020). State of the art on neural rendering. Computer Graphics Forum, 39(2), 701-727. https://doi.org/10.1111/cgf.14022
Tlili, A., Huang, R., Shehata, B., Liu, D., Zhao, J., Metwally, A. H. S., Wang, H., Denden, M., Bozkurt, A., Lee, L.-H., Beyoglu, D., Altinay, F., Sharma, R. C., Altinay, Z., Li, Z., Liu, J., Ahmad, F., Hu, Y., Salha, S., Abed, M., y Burgos, D. (2022). Is metaverse in education a blessing or a curse? A combined content and bibliometric analysis. Smart Learning Environments, 9(1), 24. https://doi.org/10.1186/s40561-022-00205-x
Waltman, L. (2016). A review of the literature on citation impact indicators. Journal of Informetrics, 10(2), 365-391. https://doi.org/10.1016/j.joi.2016.02.007
Xu, S., Wei, Y., Zheng, P., Zhang, J., y Yu, C. (2024). LLM-enabled generative collaborative design in a mixed reality environment. Journal of Manufacturing Systems, 74, 703-715. https://doi.org/10.1016/j.jmsy.2024.04.030
Yu, Q. (2022). Applying Bradford’s law to bibliometric analysis in communication and information research. Scientometrics, 127(4), 1989-2007. https://doi.org/10.1007/s11192-021-04368-5
Zhang, Y. (2023). Secure preschool education using machine learning and metaverse technologies. Applied Artificial Intelligence, 37(3), e2222496. https://doi.org/10.1080/08839514.2023.2222496