Tendencias sobre el impacto de la IA en producciones audiovisuales: un análisis bibliométrico

Autores/as

DOI:

https://doi.org/10.62008/ixc/16/01Tenden

Palabras clave:

inteligencia artificial, producción audiovisual, industria cultural, machine learning, deep learning, análisis bibliométrico

Resumen

Este artículo analiza el impacto de la inteligencia artificial en las producciones audiovisuales mediante un estudio bibliométrico de 825 artículos publicados entre 1977 y 2024. A través del análisis de redes de co-ocurrencia y la identificación de clústeres temáticos, se describen las principales líneas de investigación que articulan este campo: desde el aprendizaje profundo y la visión por computador, hasta el uso de modelos generativos en entornos creativos y culturales. El estudio propone una lectura de los periodos clave en el crecimiento de la literatura científica, atendiendo a los hitos tecnológicos que han reconfigurado la relación entre máquinas, imágenes y narrativas. Los resultados permiten no solo cartografiar el desarrollo del campo, sino también abrir nuevas líneas de reflexión sobre la autoría, la creación automatizada y el lugar de la inteligencia artificial en la cultura contemporánea.

Métricas

Cargando métricas ...

Citas

Anand, K., Gunawan, E., & Guan, Y. L. (2016). Semiblind Interference Align-ment: A New Framework. IEEE Signal Processing Letters, 23(5), 580-584. https://doi.org/10.1109/LSP.2016.2540003

Aria, M., & 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

Azarbayejani, A., Perry ,Chris, & and Pentland, A. (1997). Vision based model-ing for film and multimedia production. Applied Artificial Intelligence, 11(4), 307-330. https://doi.org/10.1080/088395197118172

Barbosa, B., Saura, J. R., Zekan, S. B., & Ribeiro-Soriano, D. (2024). RETRACTED ARTICLE: Defining content marketing and its influence on online user be-havior: a data-driven prescriptive analytics method. Annals of Operations Research, 337(S1), 17-17. https://doi.org/10.1007/s10479-023-05261-1

Behrens, R., Kupfer, A.-K., & Hennig-Thurau, T. (2024). There is business like show business! What marketing scholars and managers can learn from 40 years of entertainment science research. Journal of the Academy of Market-ing Science. https://doi.org/10.1007/s11747-024-01057-2

Bogue, R. (2022). The role of robots in entertainment. Industrial Robot: The International Journal of Robotics Research and Application, 49(4), 667-671. https://doi.org/10.1108/IR-02-2022-0054

Bory, P. (2019). Deep new: The shifting narratives of artificial intelligence from Deep Blue to AlphaGo. Convergence, 25(4), 627-642. https://doi.org/10.1177/1354856519829679

Chang, K.-W., & Chang, T.-S. (2020). VWA: Hardware Efficient Vectorwise Ac-celerator for Convolutional Neural Network. IEEE Transactions on Circuits and Systems I: Regular Papers, 67(1), 145-154. https://doi.org/10.1109/TCSI.2019.2942529

Chinnasamy, P., Deepalakshmi, P., Dutta, A., You, J., & Joshi, G. P. (2021). Ci-phertext-Policy Attribute-Based Encryption for Cloud Storage: Toward Da-ta Privacy and Authentication in AI-Enabled IoT System. Mathematics, 10, 68. https://doi.org/10.3390/math10010068

Codina, L., Morales-Vargas, A., Rodríguez-Martínez, R., & Pérez-Montoro, M. (2020). Uso de Scopus y Web of Science para investigar y evaluar en co-municación social: Análisis comparativo y caracterización. in-dex.comunicación, 10(3), Article 3. https://doi.org/10.33732/ixc/10/03Usodes

Dávila Rodríguez, M., Guzmán Sáenz, R., Macareno Arroyo, H., Piñeres Herera, D., de la Rosa Barranco, D., & Caballero-Uribe, C. V. (2009). Bibliometría: Conceptos y utilidades para el estudio médico y la formación profesional. Revista Salud Uninorte, 25(2), 319-330.

Deshpande, N., Gite, S., Pradhan, B., & Assiri, M. (2022). Explainable Artificial Intelligence–A New Step towards the Trust in Medical Diagnosis with AI Frameworks: A Review. Computer Modeling in Engineering & Sciences, 133(3), 843-872. https://doi.org/10.32604/cmes.2022.021225

Fu, M. C. (2019). Simulation-Based Algorithms for Markov Decision Processes: Monte Carlo Tree Search from AlphaGo to AlphaZero. Asia-Pacific Journal of Operational Research (APJOR), 36(06), 1-25.

Gillespie, T. (2024). Generative AI and the politics of visibility. Big Data & Soci-ety, 11(2), 20539517241252131. https://doi.org/10.1177/20539517241252131

Golbeck, J., & Klavans, J. L. (2015). Introduction to Social Media Investigation: A Hands-on Approach. Introduction to Social Media Investigation: A Hands-on Approach, 1-288.

Hansen, D., Shneiderman, B., & Smith, M. (2019). Analyzing Social Media Net-works with NodeXL: Insights from a Connected World 2nd Edition.

Huang, P. (2024). Decoding Emotions: Intelligent visual perception for movie image classification using sustainable AI in entertainment computing. En-tertainment Computing, 50, 100696. https://doi.org/10.1016/j.entcom.2024.100696

Jeon, S.-W., Kim, K., Yang, J., & Kim, D. K. (2017). The Feasibility of Interference Alignment for MIMO Interfering Broadcast—Multiple-Access Channels. IEEE Transactions on Wireless Communications, 16(7), 4614-4625. IEEE Transactions on Wireless Communications. https://doi.org/10.1109/TWC.2017.2700465

Latif, S., & Ali Najah Ahmed, A.-M. (2023). A review of deep learning and ma-chine learning techniques for hydrological inflow forecasting. Environ-ment, Development and Sustainability, 25, 1-28. https://doi.org/10.1007/s10668-023-03131-1

Ledro, C., Nosella, A., & Vinelli, A. (2022). Artificial intelligence in customer relationship management: Literature review and future research directions. Journal of Business & Industrial Marketing, 37(13), 48-63. https://doi.org/10.1108/JBIM-07-2021-0332

Li, Y. (2021). Film and TV Animation Production Based on Artificial Intelli-gence AlphaGd. Mobile Information Systems, 2021, 1-8. https://doi.org/10.1155/2021/1104248

Liu, T., Ding, X., Chen, Y., Chen, H., & Guo, M. (2016). Predicting movie Box-office revenues by exploiting large-scale social media content. Multimedia Tools and Applications, 75(3), 1509-1528. https://doi.org/10.1007/s11042-014-2270-1

López, A. C. C., Marin, A. A. L., & Pérez, M. Á. de las H. (2024). Indagación, mod-elización y pensamiento computacional: Un análisis bibliométrico con el uso de Bibliometrix a través de Biblioshiny. Revista Eureka sobre Ense-ñanza y Divulgación de las Ciencias, 21(1), Article 1. https://doi.org/10.25267/Rev_Eureka_ensen_divulg_cienc.2024.v21.i1.1102

López-Rodríguez, C. E., Calderón-Salguero, L. D., & Mora-Ortiz, M. F. (2022). La internacionalización de servicios: Análisis bibliométrico y revisión sis-temática de la literatura entre 2000 y 2021. Revista Facultad de Ciencias Económicas, 30(1), Article 1. https://doi.org/10.18359/rfce.6008

McBride, C., Lee, C. H., & Soep, E. (2024). “Gotta Love Some Human Connec-tion”: Humanizing Data Expression in an Age of AI. Reading Research Quar-terly, 59(4), 678-689. https://doi.org/10.1002/rrq.550

Palmeiro, L. L., Marin, A. A. L., Perez, M. de los A. D. las H., & López, A. C. C. (2025). Evolución del Concepto de Inteligencia Artificial en la Literatu-ra Científica: Un análisis sistemático. Digital Education Review, 46, Article 46. https://doi.org/10.1344/der.2025.46.65-76

Pardeshi, A., & Mude, D. (2024). Animating Intelligence: Impact Of AI & Ma-chine Learning Revolution In Animation. 12, c784-c797.

Punnappurath, A., Zhao, L., Abdelhamed, A., & Brown, M. S. (2024). Advocating Pixel-Level Authentication of Camera-Captured Images. IEEE Access, 12, 45839-45846. https://doi.org/10.1109/ACCESS.2024.3381521

Razavi, S. M. (2016). Unitary Beamformer Designs for MIMO Interference Broadcast Channels. IEEE Transactions on Signal Processing, 64(8), 2090-2102. IEEE Transactions on Signal Processing. https://doi.org/10.1109/TSP.2015.2508782

Reddy, V., Muthiah, K., & Reddy, V. (2023). Revolutionizing animation: Un-leashing the power of artificial intelligence for cutting-edge visual effects in films. Soft Computing, 28, 1-15. https://doi.org/10.1007/s00500-023-09448-3

Robledo-Giraldo, S., Duque-Méndez, N. D., & Zuluaga-Giraldo, J. I. (2013). Difusión de productos a través de redes sociales: Una revisión bibliográfica utilizando la teoría de grafos. Respuestas. https://revistas.ufps.edu.co/index.php/respuestas/article/view/361

Martín-Rodríguez, I & Lomba Pérez, A. (2025). Base de datos de investi-gaciones sobre el impacto de la IA en producciones audiovisuales [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.15017961

Saruthirathanaworakun, R., Le, N. T., Le, T., Srisiri, W., Chaitusaney, S., Kaew-plung, P., & Benjapolakul, W. (2024). The Application of Artificial Intelli-gence in Spectrum Management and the Analytics of Frequency Data Using Big Data Technology. IEEE Access, PP, 1-1. https://doi.org/10.1109/ACCESS.2024.3471787

Shahzad, H. F., Rustam, F., Soriano Flores, E., Vidal Mazón, J. L., Torre Díez, I. de la, & Ashraf, I. (2022). A review of image processing techniques for deep-fakes. Sensors, 22(12), 4556. https://doi.org/10.3390/s22124556

Shin, W., & Lee, J. (2015). Retrospective Interference Alignment for the Two-Cell MIMO Interfering Multiple Access Channel. IEEE Transactions on Wire-less Communications, 14(7), 3937-3947. IEEE Transactions on Wireless Communications. https://doi.org/10.1109/TWC.2015.2415474

Sidik, A. I., Komarov, R. N., Gawusu, S., Moomin, A., Al-Ariki, M. K., Elias, M., Sobolev, D., Karpenko, I. G., Esion, G., Akambase, J., Dontsov, V. V., Shafii, M., Ahlam, D., & Arzouni, N. W. (2024). Application of Artificial Intelligence in Cardiology: A Bibliometric Analysis. CUREUS JOURNAL OF MEDICAL SCI-ENCE, 16(8), e66925. https://doi.org/10.7759/cureus.66925

Singh, H., & Singh, A. (2023). ChatGPT: Systematic Review, Applications and Agenda for Multidisciplinary Research. Journal of Chinese Economic and Business Studies. https://doi.org/10.1080/14765284.2023.2210482

Song, C., Han, B., Ji, X., Li, Y., & Su, J. (2023). AI-driven Multipath Transmission: Empowering UAV-based Live Streaming. IEEE Network, PP, 1-1. https://doi.org/10.1109/MNET.2023.3321521

Tong, Y., Cao, W., Sun, Q., & Chen, D. (2021). The Use of Deep Learning and VR Technology in Film and Television Production From the Perspective of Au-dience Psychology. Frontiers in Psychology, 12. https://doi.org/10.3389/fpsyg.2021.634993

Traag, V. A., Waltman, L., & van Eck, N. J. (2019). From Louvain to Leiden: Guaranteeing well-connected communities. Scientific Reports, 9(1), 5233. https://doi.org/10.1038/s41598-019-41695-z

You, M., Chen, C., & Bu, J. (2005). CHAD: A Chinese Affective Database. En J. Tao, T. Tan, & R. W. Picard (Eds.), Affective Computing and Intelligent Interac-tion (pp. 542-549). Springer. https://doi.org/10.1007/11573548_70

Yuan, H., Lü, K., & Fang, W. (2025). Machines vs. humans: The evolving role of artificial intelligence in livestreaming e-commerce. Journal of Business Re-search, 188, 115077. https://doi.org/10.1016/j.jbusres.2024.115077

Zeng, S., Wang, C., Qin, C., & Wang, W. (2018). Interference Alignment Assisted by D2D Communication for the Downlink of MIMO Heterogeneous Net-works. IEEE Access, 6, 24757-24766. IEEE Access. https://doi.org/10.1109/ACCESS.2018.2831907

Zhang, C., Zhang, C., Li, C., Qiao, Y., Zheng, S., Dam, S., Zhang, M., Kim, J., Kim, S. T., Park, M., Choi, J., Bae, S.-H., Lee, L.-H., Hui, P., Kweon, I., & Hong, C. S. (2023). One Small Step for Generative AI, One Giant Leap for AGI: A Com-plete Survey on ChatGPT in AIGC Era. https://doi.org/10.13140/RG.2.2.24789.70883

Zhang, F., Wang, H., Zhou, L., Xu, D., & Liu, L. (2023). A blockchain-based securi-ty and trust mechanism for AI-enabled IIoT systems. Future Generation Computer Systems, 146, 78-85. https://doi.org/10.1016/j.future.2023.03.011

Zhang, Z., Tang, G., Ren, B., Li, H., & Shen, Y. (2024). TV-ADS: A Smarter Attack Detection Scheme Based on Traffic Visualization of Wireless Network Event Cell. Journal of Internet Technology, 25(2), Article 2.

Publicado

2026-01-15

Cómo citar

Martín-Rodríguez, I., & Lomba Pérez, A. (2026). Tendencias sobre el impacto de la IA en producciones audiovisuales: un análisis bibliométrico. index.Comunicación, 16(1), 99–121. https://doi.org/10.62008/ixc/16/01Tenden

Número

Sección

Monográfico 16(1)Inteligencia artificial y comunicación: transformaciones y desafíos en la era digital