Informetric analysis of the metaverse in Spanish-speaking channels and videos on YouTube
Main Article Content
Abstract
The objective is to characterize the impact in terms of views, likes and comments received for videos about the Metaverse and related terms, published and broadcast through YouTube in Spanish; and finally, to categorize the channels through which these videos related to this phenomenon have been published. For the study, a quantitative and cross-sectional descriptive informatic analysis was used on 5,479 videos published until April 10, 2022, and 822 YouTube channels. The results showed that there is a direct correlation between the views, likes, and comments of the published videos. In addition, videos under certain YouTube categories have a high impact on views despite having low volumes of publications regarding this phenomenon. It is also concluded that YouTube can be used as a data source for computer analysis along with other tools and skills.
Downloads
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
When an article is approved, the author or authors keep the rights or authorship and cede to PODIUM the right to be the first able to edit it, reproduce it, exhibit it and communicate it by printed or electronica media.
In order to reinforce our open access policy, PODIUM journal is published under a license named “Creative Commons Attribution-NonCommercial 4.0 International (CC-BY-NC 4.0)”. This license allows sharing (copying and redistributing the material in any means or format) and adapting (re-mixing, transforming, and creating starting from the material). Corresponding credits must be given and no commercial use of the materials is allowed.
Partial or complete reproduction of articles published in PODIUM is authorized, as long as the author is appropriately cited as the source and the reproduction has no commercial purposes.
References
Aich, L., y Das, A. (2021). Informetrics of Webinars Through Video Conferencing Platforms for Teaching and Learning by Different LIS Professional During COVID-19 Period: An Evaluative Study. Library Philosophy and Practice, 1-12.
Bordignon, F. R. A., Dughera, L., y Azzara, E. (2022). Revisión bibliográfica: el fenómeno YouTube y las prácticas de enseñanza y de aprendizaje. Educare, 26(1), 341-360.
Cheng, Q., Lui, C., Wai Lam Ip, F., y Siu Fai Yip, P. (2021). Typology and Impact of YouTube Videos Posted in Response to a Student Suicide Crisis: Social Media Metrics and Content Analyses. JMIR Ment Health, 8(6). DOI: 10.2196/15551
Cui, L., y Chu, L. (2021). YouTube Videos Related to the Fukushima Nuclear Disaster: Content Analysis. JMIR Public Health Surveill, 7(6). DOI: 10.2196/26481
Dowling, M. (2022). Fertile LAND: Pricing non-fungible tokens. Finance Research Letters, 44. https://doi.org/10.1016/j.frl.2021.102096
Gamboa Rodríguez, L., Iznaga Brooks, L., Fernández Wong, L., y Bailly Videaux, L. (2012). Análisis informétrico de la Revista Cubana de Ciencias de la Información en Salud, 2005 - 2010. Revista Información Científica, 73(1).
Google Developers. (2 de Julio de 2019). Getting Started with the YouTube Data API. https://developers.google.com/youtube/v3/getting-started?hl=es-419
Hosseinmardi, H., Ghasemian, A., Clauset, A., Mobius, M., Rothschild, D., y Watts, D. J. (2021). Examining the consumption of radical content on YouTube. Proceedings of the National Academy of Sciences, 118(32), 166-177. doi:10.1073/pnas.2101967118
Lee, S., Trimi, S., y Byun, W.K., y Kang, M. (2011). Innovation and imitation effects in Metaverse service adoption. Service Business, 5, 155-172. https://doi.org/10.1007/s11628-011-0108-8
Listiani, N. K. M., Suwastini, N. K. A., Dantes, G. R., Adnyani, N. L. P. S., y Jayantini, I. G. A. S. R. (2021). YouTube as Digital Learning Resources for Teaching Bilingual Young Learners. In Proceedings of the 2nd International Conference on Technology and Educational Science (ICTES 2020), 540, 156-162.
Marino, C., Lista, C., Solari, D., Spada, M., Vieno, A., y Finos, L. (2022). Predicting comments on Facebook photos: Who posts might matter more than what type of photo is posted. Addictive Behaviors Reports, 15(100417), 1-10. https://doi.org/10.1016/j.abrep.2022.100417
Onder, M. E., y Zengin, O. (2021). YouTube as a source of information on gout: a quality analysis. Rheumatology International, 41, 1321-1328. DOI: 10.1007/s00296-021-04813-7
Orduña-Malea, E., Font-Julián, C., y Ontalba-Ruipérez, J.A. (2020). Covid-19: análisis métrico de vídeos y canales de comunicación en YouTube. Profesional de la Información, 29(4). https://doi.org/10.3145/epi.2020.jul.01
Osorio Andrade, C. F., Rodríguez Orejuela, A., y Moreno Betancourt, F. (2021). Efectos de las características de videos en YouTube que aumentan su popularidad: un análisis empírico. Tendencias, 22(1), 18-38. https://doi.org/10.22267/rtend.202102.153
Park, S-M., y Kim, Y-G. (2022). A Metaverse: Taxonomy, Components, Applications, and Open Challenges. IEEE Access, 10, 4209 - 4251. DOI: 10.1109/ACCESS.2021.3140175
Reig Alamillo, A., y Elizondo Romero, A. (2018). Un análisis de la reacción me gusta en Facebook desde los estudios de la interacción. Estudios de Lingüística Aplicada, 36(67). https://doi.org/10.22201/enallt.01852647p.2018.67.722
similarweb.com. (marzo de 2022). YouTube.com. Visión general. https://www.similarweb.com/website/YouTube.com/
Stephenson, N. (1992.). Snow Crash. Bantam Books.
Suh, W., y Ahn, S. (2022). Article Utilizing the Metaverse for Learner-Centered Constructivist Education in the Post-Pandemic Era: An Analysis of Elementary School Students. Journal of Intelligence, 10(1), 17. https://doi.org/10.3390/jintelligence10010017
Taylor, C. (2022). Research on advertising in the metaverse: a call to action. International Journal of Advertising, 41(3), 383-384. DOI: 10.1080/02650487.2022.2058786
Tur-Viñes, V., Núñez-Gómez, P., y Martínez-Pastor, E. (2019). YouTube, menores y cultura colaborativa. Revisión bibliográfica de la investigación académica. Historia y Comunicación Social, 24(1), 331-351. https://doi.org/10.5209/HICS.64498
Yang, S., Yuan, Q., y Dong, J. (2020). Are Scientometrics, Informetrics, and Bibliometrics Different? Data Science and Informetrics, 1(1), 50-72. DOI: 10.4236/dsi.2020.11003
YouTube. (2022). Descripción general y requisitos del Programa para Partners de YouTube. Google Help.
Zhang, C., Ding, K., y Liu, Z. (2019). Informetric Analysis on the International Retracted Publication Based on the Web of Science Database. Advances in Social Science, Education and Humanities Research, 376, 576-585.
Zitting, K. M., Lammers-van der Holst, H. M., Yuan, R. K., Wang, W., Quan, S. F., y Duffy, J. F. (2021). Google Trends reveals increases in internet searches for insomnia during the 2019 coronavirus disease (COVID-19) global pandemic. Journal of Clinical Sleep Medicine, 17(2), 177-184. https://doi.org/10.5664/jcsm.8810
Zuckerberg, M. (28 de Octubre de 2021). Introducing Meta: A Social Technology Company. Meta.https://about.fb.com/news/2021/10/facebook-company-is-now-meta/