Deepfake: Threat or Opportunity? Creating Trustworthy Hyperreality in AI-Based Marketing-The Malaria Must Die Case
Abstract
Purpose: This research examines whether deepfake -commonly linked to deception or manipulation etc.- can be ethically reframed as a creative, emotionally persuasive tool in AI-based humanitarian marketing. Using the Malaria Must Die campaign as a case study, it analyzes how synthetic media can construct “credible hyperreality,” an aesthetic space where simulation supports authenticity, and how transparent deepfake use can convert technological risk into humanitarian opportunity.
Methodology: The research employs Multimodal Discourse Analysis (MDA) grounded in Kress and van Leeuwen’s social semiotic framework. The advertisement was segmented into sequences and analyzed across visual, linguistic, auditory, and cinematographic modes. Sub-modes (framing, salience, information value, gesture, soundtrack, color, deepfake transitions) were coded to reveal meaning-making patterns. The research interprets multimodal composition rather than measuring audience reception.
Results: Three primary narrative modes emerged: (1) ethical simulation, reframing deepfake as moral amplification; (2) polyphonic participation, realized through Beckham’s multilingual synthetic performance representing diverse voices; and (3) aesthetic realism, produced via warm palettes, intimate domestic settings, and intersemiotic coherence. Together these modes generate credible hyperreality-an emotionally authentic and ethically framed simulated narrative.
Originality: The research repositions deepfake from a manipulation paradigm toward responsible mediation that can produce emotional authenticity in humanitarian communication. By integrating Baudrillard’s hyperreality with multimodal analysis, it offers a novel theoretical lens on synthetic media and demonstrates how deepfake can ethically enhance empathy, solidarity, and global engagement.
Keywords: Deepfake; Multimodal Discourse Analysis; Hyperreality; AI-based Marketing; Humanitarian Communication; Ethical Simulation.
DOI: https://doi.org/10.58869/SPM/04
Full Text:
PDFReferences
Atalay, G. E. (2015, July). Use of multimodal critical discourse analysis in media studies. ResearchGate. https://www.researchgate.net/publication/327885258_USE_OF_MULTIMODAL_CRITICAL_DISCOUSE_ANALYSIS_IN_MEDIA_STUDIES
Baudrillard, J. (2024). Simülakrlar ve simülasyon. (O. Adanır, Trans.) DOĞUBATI.
BBC. (2019). How AI is bringing film stars back from the dead. BBC. https://www.bbc.com/future/article/20230718-how-ai-is-bringing-film-stars-back-from-the-dead
Campbell, C., Plangger, K., Sands, S., & Kietzmann, J. (2021). Preparing for an era of deep fakes and AI-generated ads: A framework for understanding responses to manipulated advertising. Journal of Advertising, 51(1), 1-17.
Chadha, A., Kumar, V., Kashyap, S., & Gupta, M. (2021). Deepfake: An overview. In Proceedings of Second International Conference on Computing, Communications, and Cyber-Security: IC4S 2020 (pp. 557-566). Springer Singapore.
Chi, O. H., Chi, C. G., Gursoy, D., & Nunkoo, R. (2023). Customers’ acceptance of artificially intelligent service robots: The influence of trust and culture. International Journal of Information Management, 73, 102623. https://doi.org/10.1016/j.ijinfomgt.2023.102623
Citron, D. K., Chesney, R. (2018). Deep fakes: a looming challenge for privacy, Boston University School of Law, 1-58.
Dash, A. K., Patnaik, P., & Suar, D. (2016). A multimodal discourse analysis of glocalization and cultural identity in three Indian TV commercials. Discourse & Communication, 10(3), 209–234. https://doi.org/10.1177/1750481315623892
Dolhansky, B., Bitton, J., Pflaum, B., Lu, J., Howes, R., Wang, M., & Ferrer, C. C. (2020). The deepfake detection challenge (DFDC) dataset. arXiv preprint arXiv:2006.07397. https://doi.org/10.48550/arXiv.2006.07397
Fagni, T., Falchi, F., Gambini, M., Martella, A., & Tesconi, M. (2021). TweepFake: About detecting deepfake tweets. PLoS ONE, 16(5), e0251415. https://doi.org/10.1371/journal.pone.0251415
International Telecommunication Union. (2025). AI for Good Global Summit 2025. AI for Good. https://aiforgood.itu.int/summit25/
İplikçi, H. G. (2015). Reklamlarda tüketiciyi ikna etmek için kullanılan stratejiler ve reklam örnekleri. Sosyal ve Beşeri Bilimler Dergisi, 7(1), 65-77.
Kietzmann, J., Mills, A. J., & Plangger, K. (2021). Deepfakes: Perspectives on the future “reality” of advertising and branding. International Journal of Advertising, 40(3), 473-485.
Kress, G. (2005). Gains and losses: New forms of texts, knowledge, and learning. Computers and Composition, 22 (1), 5-22. https://doi.org/10.1016/j.compcom.2004.12.004
Kress, G., & van Leeuwen, T. (2006). Reading images: The grammar of visual design (2nd ed.). Routledge.
Malaria Must Die. (2019, April 9). David Beckham speaks nine languages to launch Malaria Must Die Voice Petition [Video]. YouTube. https://www.youtube.com/watch?v=QiiSAvKJIHo
Malaria Must Die. (2025, March 5). We're an award-winning campaign. Malaria Must Die. https://malariamustdie.com/news/an-award-winning-campaign
Malaria No More UK. (2019). Our voice petition film with David Beckham wins award. https://malarianomore.org.uk/we-won-award-david-beckham film#:~:text=Our%20voice%20petition%20film%20with,take%20action%20to%20defeat%20malaria
Moustakas, E., Lamba, N., Mahmoud, D., & Ranganathan, C. (2020). Blurring lines between fiction and reality: Perspectives of experts on marketing effectiveness of virtual influencers. In 2020 International Conference on Cyber Security and Protection of Digital Services (Cyber Security) (pp. 1–8). IEEE.
https://doi.org/10.1109/CyberSecurity49315.2020.9138861
Mukhroji, M., Nurkamto, J., Subroto, H. E., & Tardjana, S. S. (2019). Pragmatic forces in the speech acts of EFL speakers at Kampung Inggris, Indonesia. Journal of Social Studies Education Research, 10(1), 38–60.
Rosner, H. (2021, July 5). A haunting new documentary about Anthony Bourdain. The New Yorker. https://www.newyorker.com/culture/annals-of-gastronomy/the-haunting-afterlife-of-anthonybourdain
Rubin, M., Li, J. Z., Zimmerman, F., et al. (2025). Comparing the value of perceived human versus AI-generated empathy. Nature Human Behaviour. https://doi.org/10.1038/s41562-025-02247-w
Ruiz, N., Bargal, S. A., & Sclaroff, S. (2020). Disrupting deepfakes: Adversarial attacks against conditional image translation networks and facial manipulation systems. arXiv preprint arXiv:2003.01279. https://doi.org/10.48550/arXiv.2003.01279
Smith, D. A. (2020). Deepfake videos are getting real and that’s a problem. The Guardian. https://www.theguardian.com/technology/2020/feb/01/deepfake-videos-trump-2020-election-joe-biden
Solak, B.B. (2016). Televizyon reklamlarında ünlü kullanımının satın alma davranışı üzerine etkisi: Akdeniz Üniversitesi İletişim Fakültesi öğrencilerine yönelik araştırma. Gümüşhane Üniversitesi İletişim Fakültesi Elektronik Dergisi, 4 (1), 253-278.
Synthesia. (2019). Case study – David Beckham / Malaria No More / RGA. Synthesia. https://www.synthesia.io/case-studies/malaria-no-more
Synthesia. (2025, March 5). How we made David Beckham speak 9 languages. Synthesia. https://www.synthesia.io/post/david-beckham
Taş, O. & Taş, T. (2018). Post-hakikat çağında sosyal medyada yalan haber ve Suriyeli mülteciler sorunu. İletişim, 29 (29), 183 - 208.
Tayfur, G. (2008). Reklamcılık. Nobel.
Tuncer, E. S. (2022). Reklam göstergebilimi. Kriter.
UNICEF Türkiye. (2025, March 5). Afrika ülkelerinde sıtmayla mücadelede yeni adımlar. UNICEF Türkiye. https://www.unicefturk.org/yazi/afrika-ulkelerinde-sitmayla-mucadele
United Nations Development Programme. (2025). Sustainable Development Goals. UNDP. https://www.undp.org/sustainable-development-goals
Whittaker, L., Mulcahy, R., Russell-Bennett, R., Letheren, K., & Kietzmann, J. (2025). Examining consumer appraisals of deepfake advertising and disclosure: Show deepfakes as “real life” or say they’re “just fantasy”? Journal of Advertising Research, 1–22. https://doi.org/10.1080/00218499.2025.2498830
Yolcu, E. (2002). Renklerin öznel kullanımı ve ekinsel olarak algılanması. İstanbul Üniversitesi İletişim Fakültesi Dergisi, 659.
Yu, P., Xia, Z., Fei, J., & Lu, Y. (2021). A survey on deepfake video detection. IET Biometrics, 10 (6), 607-624.
Zhao, H., Zhou, W., Chen, D., Wei, T., Zhang, W., & Yu, N. (2021). Multi-attentional deepfake detection. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 2185-2194).
Copyright (c) 2026 European Journal of Applied Business and Management
European Journal of Applied Business and Management
ISSN: 2183-5594
DOI: https://doi.org/10.58869/EJABM
Indexing:
EBSCO | CROSSREF | GOOGLE SCHOLAR | LATINDEX | DRJI | ICI JOURNALS MASTER | REDIB | MIAR
.jpeg)

.jpeg)

.jpeg)
.jpeg)
.png)
3.png)
1.png)
.png)
