Research Article

Exploring the impact of visual components on the perceived realism of generative AI videos

Alberto Sanchez-Acedo 1 , Alejandro Carbonell-Alcocer 1 * , Pasquale Cascarano 2 , Shirin Hajahmadi 3 , Manuel Gertrudix 1 , Gustavo Marfia 3
More Detail
1 Department of Audiovisual Communication and Advertising, Rey Juan Carlos University, Madrid, SPAIN2 Department of the Arts, University of Bologna, Bologna, ITALY3 Department of Computer Science and Engineering, University of Bologna, Bologna, ITALY* Corresponding Author
Online Journal of Communication and Media Technologies, 16(1), January 2026, e202603, https://doi.org/10.30935/ojcmt/17737
Published: 14 January 2026
OPEN ACCESS   492 Views   211 Downloads
Download Full Text (PDF)

ABSTRACT

Generative artificial intelligence (Gen-AI) tools have a significant impact on the creation of audiovisual content. Although these tools are still at an early stage in video production, there are tools such as Sora (OpenAI) that demonstrate the great potential of Gen-AI to create advanced audiovisual content. This study evaluates through a comparative analysis the level of realism, attractiveness and composition of the videos generated by Sora compared to real videos. Using a questionnaire validated by experts (n = 12), a quasi-experiment was conducted with college students (n = 62) who were divided into two groups: a control group that visualized real videos from YouTube and an experimental group that visualized videos created with the Sora tool. The results show that attractiveness, particularly the elements of lighting, saturation and color, are key factors in the recognition of a Gen-AI video. The paper concludes that Gen-AI tools should focus on improving the attractive elements to achieve more consistent and natural results.
Keywords: artificial intelligence, Sora, AI video generation, text-to-video, audiovisual analysis, quasi-experiment

CITATION (APA)

Sanchez-Acedo, A., Carbonell-Alcocer, A., Cascarano, P., Hajahmadi, S., Gertrudix, M., & Marfia, G. (2026). Exploring the impact of visual components on the perceived realism of generative AI videos. Online Journal of Communication and Media Technologies, 16(1), e202603. https://doi.org/10.30935/ojcmt/17737

REFERENCES

  1. Abeliuk, A., & Gutiérrez, C. (2021). Historia y evoluación de la inteligencia artificial [History and evolution of artificial intelligence]. Revista Bits de Ciencia, (21), 14-21. https://doi.org/10.71904/bits.vi21.2767
  2. Achi, M. C. R. (2004). Manual de formación audiovisual [Audiovisual training manual]. Cholsamaj Fundacion.
  3. Adetayo, A. J., Enamudu, A. I., Lawal, F. M., & Odunewu, A. O. (2024). From text to video with AI: The rise and potential of Sora in education and libraries. Library Hi Tech News. https://doi.org/10.1108/LHTN-02-2024-0028
  4. Alasadi, E. A., & Baiz, C. R. (2023). Generative AI in education and research: Opportunities, concerns, and solutions. Journal of Chemical Education, 100(8), 2965-2971. https://doi.org/10.1021/acs.jchemed.3c00323
  5. Ara, A., & Ara, A. (2024). Exploring the ethical implications of generative AI. IGI Global. https://doi.org/10.4018/979-8-3693-1565-1
  6. Babl, F. E., & Babl, M. P. (2023). Generative artificial intelligence: Can ChatGPT write a quality abstract? Emergency Medicine Australasia, 35(5), 809-811. https://doi.org/10.1111/1742-6723.14233
  7. Batista, A. R. F., & Santaella, L. (2023). IAs generativas: A importância dos comandos para texto e imagem [Generative AIs: The importance of commands for text and images.]. Aurora. Revista de Arte, Mídia e Política, 16(47), 76-94. https://doi.org/10.23925/1982-6672.2023v16i47p76-94
  8. Belloch, C. (2012). Las tecnologías de la información y comunicación en el aprendizaje [Information and communication technologies in learning]. Depto MIDE. Universidad de Valencia, 4, 1-11. https://www.uv.es/bellochc/pedagogia/EVA1.pdf
  9. Betker, J., Goh, G., Jing, L., Brooks, T., Wang, J., Li, L., Ouyang, L., Zhuang, J., Guo, Y., Manassra, W., Dhariwal, P., Chu, C., Jiao, Y., & Ramesh, A. (2023). Improving image generation with better captions. Computer Science, 2(3).
  10. Bewersdorff, A., Hartmann, C., Hornberger, M., Seßler, K., Bannert, M., Kasneci, E., Kasneci, G., Zhai, X., & Nerdel, C. (2025). Taking the next step with generative artificial intelligence: The transformative role of multimodal large language models in science education. Learning and Individual Differences, 118, Article 102601. https://doi.org/10.1016/j.lindif.2024.102601
  11. Bijalwan, P., Gupta, A., Johri, A., Wasiq, M., & Khalil Wani, S. (2025). Unveiling sora open AI’s impact: A review of transformative shifts in marketing and advertising employment. Cogent Business & Management, 12(1), Article 2440640. https://doi.org/10.1080/23311975.2024.2440640
  12. Brooks, T., Peebles, B., Holmes, C., DePue, W., Guo, Y., Jing, L., Schnurr, D., Taylor, J., Luhman, T., Luhman, E., Ng, C., Wang, R., & Ramesh, A. (2024). Video generation models as world simulators. OpenAI. https://openai.com/research/video-generation-models-as-world-simulators
  13. Cao, Y., Li, S., Liu, Y., Yan, Z., Dai, Y., Yu, P. S., & Sun, L. (2023). A comprehensive survey of AI-generated content (AIGC): A history of generative AI from GAN to ChatGPT. arXiv. https://doi.org/10.48550/arXiv.2303.04226
  14. Carbonell-Alcocer, A., Sanchez-Acedo, A., Benitez-Aranda, N., & Gertrudix,M. (2025). Impacto de la inteligencia artificial generativa en la eficiencia, calidad e innovación en la producción de recursos educativos abiertos para MooCs [Impact of generative artificial intelligence on efficiency, quality and innovation in the production of open educational resources for MOOCs]. Comunicación y Sociedad, (22), e8785. https://doi.org/10.32870/cys.v2025.8784
  15. Celik, I. (2023). Towards Intelligent-TPACK: An empirical study on teachers’ professional knowledge to ethically integrate artificial intelligence (AI)-based tools into education. Computers in Human Behavior, 138, Article 107468. https://doi.org/10.1016/j.chb.2022.107468
  16. Chen, Z., Li, S., & Haque, M. A. (2024). An overview of OpenAI’s Sora and its potential for physics engine free games and virtual reality. EAI Endorsed Transactions on AI and Robotics, 3. https://doi.org/10.4108/airo.5273
  17. Cho, J., Puspitasari, F. D., Zheng, S., Zheng, J., Lee, L. H., Kim, T. H., Hong, C. S., & Zhang, C. (2024). Sora as an AGI world model? A complete survey on text-to-video generation. arXiv. https://doi.org/10.48550/arXiv.2403.05131
  18. Dempere, J., Modugu, K., Hesham, A., & Ramasamy, L. K. (2023). The impact of ChatGPT on higher education. Frontiers in Education, 8. https://doi.org/10.3389/feduc.2023.1206936
  19. Díaz-Rodríguez, N., Del Ser, J., Coeckelbergh, M., de Prado, M. L., Herrera-Viedma, E., & Herrera, F. (2023). Connecting the dots in trustworthy artificial intelligence: From AI principles, ethics, and key requirements to responsible AI systems and regulation. Information Fusion, 99, Article 101896. https://doi.org/10.1016/j.inffus.2023.101896
  20. Doshi, A. R., & Hauser, O. (2023). Generative artificial intelligence enhances creativity but reduces the diversity of novel content. SSRN. https://doi.org/10.2139/ssrn.4535536
  21. Epstein, Z., Hertzmann, A., & Investigators of Human Creativity. (2023). Art and the science of generative AI. Science, 380(6650), 1110-1111. https://doi.org/10.1126/science.adh4451
  22. Escobar-Pérez, J., & Cuervo-Martínez, Á. (2008). Validez de contenido y juicio de expertos: Una aproximación a su utilización [Content validity and expert judgment: An approach to their use]. Avances en Medición, 6(1), 27-36. https://www.humanas.unal.edu.co/lab_psicometria/application/files/9416/0463/3548/Vol_6._Articulo3_Juicio_de_expertos_27-36.pdf
  23. Espacio Telefónica. (2023). Fake news. La fábrica de mentiras. https://bit.ly/3Q0SwNH
  24. Fan, S., Ng, T. T., Koenig, B. L., Herberg, J. S., Jiang, M., Shen, Z., & Zhao, Q. (2017). Image visual realism: From human perception to machine computation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 40(9), 2180-2193. https://doi.org/10.1109/TPAMI.2017.2747150
  25. Fernández Mateo, J. (2023). Realidad artificial. Un análisis de las potenciales amenazas de la inteligencia artificial [Artificial reality. An analysis of the potential threats of artificial intelligence]. Revista Internacional de Cultura Visua,l 9(2). https://doi.org/10.37467/revvisual.v9.5004
  26. Fijačko, N., Štiglic, G., Topaz, M., & Greif, R. (2025). Using OpenAI’s text-to-video model Sora to generate cardiopulmonary resuscitation content. Resuscitation, 207. https://doi.org/10.1016/j.resuscitation.2024.110484
  27. Fui-Hoon Nah, F., Zheng, R., Cai, J., Siau, K., & Chen, L. (2023). Generative AI and ChatGPT: Applications, challenges, and AI-human collaboration. Journal of Information Technology Case and Application Research, 25(3), 277-304. https://doi.org/10.1080/15228053.2023.2233814
  28. Galvez Martínez, C. (2024). Mapa científico de la inteligencia artificial en comunicación (2004-2024) [Scientific map of artificial intelligence in communication (2004-2024)]. European Public & Social Innovation Review, 9, 1-17. https://doi.org/10.31637/epsir-2024-947
  29. García-Peñalvo, F. J. (2023). La percepción de la inteligencia artificial en contextos educativos tras el lanzamiento de ChatGPT: Disrupción o pánico [The perception of artificial intelligence in educational contexts after the launch of ChatGPT: Disruption or panic]. Education in the Knowledge Society, 24, e31279-e31279. https://doi.org/10.14201/eks.31279
  30. García-Peñalvo, F. J., Llorens-Largo, F., & Vidal, J. (2024). La nueva realidad de la educación ante los avances de la inteligencia artificial generative [The new reality of education in the face of advances in generative artificial intelligence]. RIED-Revista Iberoamericana de Educación a Distancia, 27(1), 9-39. https://doi.org/10.5944/ried.27.1.37716
  31. Go Places Pro (2021). Santorini, Greece-4K UHD drone video. YouTube. https://www.youtube.com/watch?v=rXlqSYZOGnQ&t=456s
  32. González Arencibia, M., & Martínez Cardero, D. (2020). Dilemas éticos en el escenario de la inteligencia artificial [Ethical dilemmas in the artificial intelligence scenario]. Economía y Sociedad, 25(57), 93-109. https://doi.org/10.15359/eys.25-57.5
  33. Herath, D. B., Ode, E., & Herath, G. B. (2025). Can AI replace humans? Comparing the capabilities of AI tools and human performance in a business management education scenario. British Educational Research Journal, 51(3), 1073-1096. https://doi.org/10.1002/berj.4111
  34. Joosten, J., Bilgram, V., Hahn, A., & Totzek, D. (2024). Comparing the ideation quality of humans with generative artificial intelligence. IEEE Engineering Management Review, 52(2), 153-164. https://doi.org/10.1109/EMR.2024.3353338
  35. Kalyan, K. S. (2023). A survey of GPT-3 family large language models including ChatGPT and GPT-4. Natural Language Processing Journal, 6, Article 100048. https://doi.org/10.1016/j.nlp.2023.100048
  36. Kim, J. G. (2024). Current use and issues of generative AI in the film industry. Journal of Information Technology Applications and Management, 31(3), 181-192. https://doi.org/10.21219/jitam.2024.31.3.181
  37. Kustudic, M., & Mvondo, G. F. N. (2024). A hero or a killer? Overview of opportunities, challenges, and implications of text-to-video model SORA. Authorea. https://doi.org/10.36227/techrxiv.171207528.88283144/v1
  38. Leivada, E., Murphy, E., & Marcus, G. (2023). DALL· E 2 fails to reliably capture common syntactic processes. Social Sciences & Humanities Open, 8(1), Article 100648. https://doi.org/10.1016/j.ssaho.2023.100648
  39. Liu, Y., Zhang, K., Li, Y., Yan, Z., Gao, C., Chen, R., Yuan, Z., Huang, Y., Sun, H., Gao, J., He, L., & Sun, L. (2024). Sora: A review on background, technology, limitations, and opportunities of large vision models. arXiv. https://doi.org/10.48550/arXiv.2402.17177
  40. Medina-Romero, M. Á. (2023). Las herramientas de inteligencia artificial orientadas al fortalecimiento del desarrollo de investigaciones científicas y académicas: El caso de Smartpaper [Artificial intelligence tools aimed at strengthening the development of scientific and academic research: The Smartpaper case]. Ciencia Latina Revista Científica Multidisciplinar, 7(3). https://doi.org/10.37811/cl_rcm.v7i3.6743
  41. Mogavi, R. H., Wang, D., Tu, J., Hadan, H., Sgandurra, S. A., Hui, P., & Nacke, L. E. (2024). Sora OpenAI’s prelude: Social media perspectives on Sora OpenAI and the future of AI video generation. arXiv. https://doi.org/10.48550/arXiv.2403.14665
  42. Motlagh, N. Y., Khajavi, M., Sharifi, A., & Ahmadi, M. (2023). The impact of artificial intelligence on the evolution of digital education: A comparative study of openAI text generation tools including ChatGPT, Bing Chat, Bard, and Ernie. arXiv. https://doi.org/10.48550/arXiv.2309.02029
  43. Mvondo, G. F. N., & Niu, B. (2024). Factors influencing user willingness to use SORA. arXiv. https://doi.org/10.48550/arXiv.2405.03986
  44. Obrenovic, B., Gu, X., Wang, G., Godinic, D., & Jakhongirov, I. (2024). Generative AI and human-robot interaction: Implications and future agenda for business, society and ethics. AI & SOCIETY, 40, 677-690. https://doi.org/10.1007/s00146-024-01889-0
  45. OpenAI, Achiam, J., Adler, S., Agarwal, S., Ahmad, L., Akkaya, I., Aleman, F. L., Almeida, D., Altenschmidt, J., Altman, S., Anadkat, S., Avila, R., babuschkin, I., Balaji, S., Balcom, V., Baltescu, P., Bao, H., Bavarian, M., Belgum, J., … Zoph, B. (2023). GPT-4 technical report. arXiv. https://doi.org/10.48550/arXiv.2303.08774
  46. OpenAI. (2024a). Creating video from text sora is an ai model that can create realistic and imaginative scenes from text instructions. OpenAI. https://openai.com/index/sora/
  47. OpenAI. (2024b). OpenAI and Apple announce partnership to integrate ChatGPT into Apple experiences. OpenAI. https://openai.com/index/openai-and-apple-announce-partnership/
  48. Owan, V. J., Abang, K. B., Idika, D. O., Etta, E. O., & Bassey, B. A. (2023). Exploring the potential of artificial intelligence tools in educational measurement and assessment. Eurasia Journal of Mathematics, Science and Technology Education, 19(8), Article em2307. https://doi.org/10.29333/ejmste/13428
  49. Peebles, W., & Xie, S. (2023). Scalable diffusion models with transformers. In Proceedings of the IEEE/CVF International Conference on Computer Vision (pp. 4195-4205). IEEE. https://doi.org/10.1109/ICCV51070.2023.00387
  50. Prieto-Gutierrez, J. J., Segado-Boj, F., & Da Silva França, F. (2024). Artificial intelligence in social science: A study based on bibliometrics analysis. Human Technology, 19(2), 149-162. https://doi.org/10.14254/1795-6889.2023.19-2.1
  51. Putland, E., Chikodzore-Paterson, C., & Brookes, G. (2025). Artificial intelligence and visual discourse: A multimodal critical discourse analysis of AI-generated images of “Dementia”. Social Semiotics, 35(2), 228-253. https://doi.org/10.1080/10350330.2023.2290555
  52. Ramos-Galarza, C. (2021). Editorial: Diseños de investigación experimental [Editorial: Experimental research designs]. CienciaAmerica, 10(1), 1-7. https://doi.org/10.33210/ca.v10i1.356
  53. Ryan Shirley. (2021). Top 10 places on the Amalfi Coast-4K travel guide. YouTube. https://www.youtube.com/watch?v=Mupom-sgjAU
  54. Sanchez-Acedo, A., Carbonell-Alcocer, A., Cascarano, P., Hajahmadi S., Gertrudix, M., & Marfia, G. (2024). Materials for the validation of a cuasiexperiment on Gen-AI. Zenodo. https://doi.org/10.5281/zenodo.13893803
  55. Sánchez-García, P., Merayo-Álvarez, N., Calvo-Barbero, C., & Diez-Gracia, A. (2023). Spanish technological development of artificial intelligence applied to journalism: Companies and tools for documentation, production and distribution of information. Profesional de la Información, 32(2). https://doi.org/10.3145/epi.2023.mar.08
  56. Sarkar, N. I., & Gul, S. (2023). Artificial intelligence-based autonomous UAV networks: A survey. Drones, 7(5), Article 322. https://doi.org/10.3390/drones7050322
  57. Suárez-Roca, J. E., & Vélez-Bermello, G. L. (2022). Verificación de los hechos: Aplicación metodológica en el medio de comunicación El Bacán [Fact-checking: Methodological application in the media outlet El Bacán]. Revista Científica Arbitrada de Investigación en Comunicación, Marketing y Empresa REICOMUNICAR, 5(9), 163-184. https://doi.org/10.46296/rc.v5i9.0042
  58. Sun, R., Zhang, Y., Shah, T., Sun, J., Zhang, S., Li, W., Duan, H., Wei, B., & Ranjan, R. (2024). From Sora what we can see: A survey of text-to-video generation. arXiv. https://doi.org/10.48550/arXiv.2405.10674
  59. Wach, K., Duong, C. D., Ejdys, J., Kazlauskaitė, R., Korzynski, P., Mazurek, G., Paliszkiewicz, J., & Ziemba, E. (2023). The dark side of generative artificial intelligence: A critical analysis of controversies and risks of ChatGPT. Entrepreneurial Business and Economics Review, 11(2), 7-30. https://doi.org/10.15678/EBER.2023.110201
  60. Wang, W., & Yang, Y. (2024). VidProM: A million-scale real prompt-gallery dataset for text-to-video diffusion models. In Proceedings of the Advances in Neural Information Processing Systems 37. NeurlPS. https://doi.org/10.52202/079017-2096
  61. Wolf, T., Debut, L., Sanh, V., Chaumond, J., Delangue, C., Moi, A., Cistac, P., Rault, T., Louf, R., Funtowicz, M., Davison, J., Shleifer, S., von Platen, P., Ma, C., Jernite, Y., Plu, J., Le Scao, T., Gugger, S., ... & Rush, A. M. (2020). Transformers: State-of-the-art natural language processing. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations (pp. 38-45). https://doi.org/10.18653/v1/2020.emnlp-demos.6
  62. Zhai, X. (2023). ChatGPT for next generation science learning. The ACM Magazine for Students, 29(3), 42-46. https://doi.org/10.1145/3589649
  63. Zhao, W. X., Zhou, K., Li, J., Tang, T., Wang, X., Hou, Y., Min, Y., Zhang, B., Zhang, J., Dong, Z., Du, Y., Yang, C., Chen, Y., Chen, Z., Jiang, J., Ren, R., Li, Y., Tang, X., Liu, Z., ... Wen, J. R. (2023). A survey of large language models. arXiv. https://doi.org/10.48550/arXiv.2303.18223
  64. Zhou, K. Z., Choudhry, A., Gumusel, E., & Sanfilippo, M. R. (2024). ‘Sora is incredible and scary’: Emerging governance challenges of text-to-video generative AI models. Information Research an International Electronic Journal, 30(iConf), 508-522. https://doi.org/10.47989/ir30iConf47290
  65. Zwakman, D. S., Pal, D., & Arpnikanondt, C. (2021). Usability evaluation of artificial intelligence-based voice assistants: The case of Amazon Alexa. SN Computer Science, 2, 1-16. https://doi.org/10.1007/s42979-020-00424-4