Aesthetics of Disinformation in Digital News Circulation
Multimodal Analysis of False Visual Tests
DOI:
https://doi.org/10.62161/revvisual.v18.6396Keywords:
Visual disinformation, Multimodal analysis, Evidentiality, Recontextualization, Deepfakes, Fact-checking, Composite montagesAbstract
This study examines the aesthetics of disinformation in news by analyzing 60 fake visual pieces (recontextualized screenshots, composite montages, and synthetic/manipulated content) collected from the Spanish-language digital news ecosystem (2024-2025). Through multimodal analysis, it identifies five recurrent clusters of evidential cues (provenance/authority, news urgency, interface/screenshot, probative pointing, documentality) and text-image anchoring patterns that construct the appearance of evidence. The “aesthetic of proof” operates as an assembly of provenance markers, news design, and reading guides, providing criteria for verification and visual literacy.
Downloads
Global Statistics ℹ️
|
140
Views
|
64
Downloads
|
|
204
Total
|
|
References
Aljalabneh, A. A. (2024). Visual media literacy: Educational strategies to combat image and video disinformation on social media. Frontiers in Communication, 9, 1490798. https://doi.org/10.3389/fcomm.2024.1490798 DOI: https://doi.org/10.3389/fcomm.2024.1490798
Altay, S., & Gilardi, F. (2024). People are skeptical of headlines labeled as AI-generated, even if true or human-made, because they assume full AI automation. PNAS Nexus, 3(10), pgae403. https://doi.org/10.1093/pnasnexus/pgae403 DOI: https://doi.org/10.1093/pnasnexus/pgae403
Appel, M., & Prietzel, F. (2022). The detection of political deepfakes. Journal of Computer-Mediated Communication, 27(4), zmac008. https://doi.org/10.1093/jcmc/zmac008 DOI: https://doi.org/10.1093/jcmc/zmac008
Brennen, J. S., Simon, F. M., & Nielsen, R. K. (2021). Beyond (Mis)Representation: Visuals in COVID-19 Misinformation. The International Journal of Press/Politics, 26(1), 277-299. https://doi.org/10.1177/1940161220964780 DOI: https://doi.org/10.1177/1940161220964780
Broda, E., & Strömbäck, J. (2024). Misinformation, disinformation, and fake news: Lessons from an interdisciplinary, systematic literature review. Annals of the International Communication Association, 48(2), 139-166. https://doi.org/10.1080/23808985.2024.2323736 DOI: https://doi.org/10.1080/23808985.2024.2323736
Chadwick, A., & Stanyer, J. (2022). Deception as a Bridging Concept in the Study of Disinformation, Misinformation, and Misperceptions: Toward a Holistic Framework. Communication Theory, 32(1), 1-24. https://doi.org/10.1093/ct/qtab019 DOI: https://doi.org/10.1093/ct/qtab019
Fisher, S. A. (2025). Something AI Should Tell You – The Case for Labelling Synthetic Content. Journal of Applied Philosophy, 42(1), 272-286. https://doi.org/10.1111/japp.12758 DOI: https://doi.org/10.1111/japp.12758
Gehrke, M., Eggers, J., De Vreese, C., & Hopmann, D. N. (2025). What Makes News (Seem) Authentic on Social Media? Indicators from a Qualitative Study of Young Adults. Digital Journalism, 13(8), 1503-1522. https://doi.org/10.1080/21670811.2024.2399622 DOI: https://doi.org/10.1080/21670811.2024.2399622
Gërguri, D. (2025). Cheapfakes. En A. Nai, M. Grömping, & D. Wirz (Eds.), Elgar Encyclopedia of Political Communication (pp. 192-195). Edward Elgar Publishing. https://doi.org/10.4337/9781035301447.vol1.00053 DOI: https://doi.org/10.4337/9781035301447.vol1.00053
Gillespie, T. (2022). Do Not Recommend? Reduction as a Form of Content Moderation. Social Media + Society, 8(3), 20563051221117552. https://doi.org/10.1177/20563051221117552 DOI: https://doi.org/10.1177/20563051221117552
Habgood-Coote, J. (2023). Deepfakes and the epistemic apocalypse. Synthese, 201(3), 103. https://doi.org/10.1007/s11229-023-04097-3 DOI: https://doi.org/10.1007/s11229-023-04097-3
Hameleers, M. (2024). Cheap Versus Deep Manipulation: The Effects of Cheapfakes Versus Deepfakes in a Political Setting. International Journal of Public Opinion Research, 36(1), edae004. https://doi.org/10.1093/ijpor/edae004 DOI: https://doi.org/10.1093/ijpor/edae004
Hameleers, M. (2025). The Nature of Visual Disinformation Online: A Qualitative Content Analysis of Alternative and Social Media in the Netherlands. Political Communication, 42(1), 108-126. https://doi.org/10.1080/10584609.2024.2354389 DOI: https://doi.org/10.1080/10584609.2024.2354389
Hameleers, M., & Marquart, F. (2023). It’s Nothing but a Deepfake! The Effects of Misinformation and Deepfake Labels Delegitimizing an Authentic Political Speech. International Journal of Communication, 17, 21-21.
Hameleers, M., Powell, T. E., Van Der Meer, T. G. L. A., & Bos, L. (2020). A Picture Paints a Thousand Lies? The Effects and Mechanisms of Multimodal Disinformation and Rebuttals Disseminated via Social Media. Political Communication, 37(2), 281-301. https://doi.org/10.1080/10584609.2019.1674979 DOI: https://doi.org/10.1080/10584609.2019.1674979
Hausken, L. (2024). Photorealism versus photography. AI-generated depiction in the age of visual disinformation. Journal of Aesthetics & Culture, 16(1), 2340787. https://doi.org/10.1080/20004214.2024.2340787 DOI: https://doi.org/10.1080/20004214.2024.2340787
Heley, K., Gaysynsky, A., & King, A. J. (2022). Missing the Bigger Picture: The Need for More Research on Visual Health Misinformation. Science Communication, 44(4), 514-527. https://doi.org/10.1177/10755470221113833 DOI: https://doi.org/10.1177/10755470221113833
Köbis, N. C., Doležalová, B., & Soraperra, I. (2021). Fooled twice: People cannot detect deepfakes but think they can. iScience, 24(11), 103364. https://doi.org/10.1016/j.isci.2021.103364 DOI: https://doi.org/10.1016/j.isci.2021.103364
Kress, G. R., & Van Leeuwen, T. (2020). Reading images: The grammar of visual design (Third edition). Routledge. DOI: https://doi.org/10.4324/9781003099857
Kress, G., & Van Leeuwen, T. (2020). Reading Images: The Grammar of Visual Design (3.a ed.). Routledge. https://doi.org/10.4324/9781003099857 DOI: https://doi.org/10.4324/9781003099857
Lecheler, S., & Egelhofer, J. L. (2022). Disinformation, Misinformation, and Fake News: Understanding the Supply Side. En Knowledge Resistance in High-Choice Information Environments. Routledge. DOI: https://doi.org/10.4324/9781003111474-4
Mirsky, Y., & Lee, W. (2022). The Creation and Detection of Deepfakes: A Survey. ACM Computing Surveys, 54(1), 1-41. https://doi.org/10.1145/3425780 DOI: https://doi.org/10.1145/3425780
Newman, E. J., & Schwarz, N. (2024). Misinformed by images: How images influence perceptions of truth and what can be done about it. Current Opinion in Psychology, 56, 101778. https://doi.org/10.1016/j.copsyc.2023.101778 DOI: https://doi.org/10.1016/j.copsyc.2023.101778
Peng, Y., Lu, Y., & Shen, C. (2023). An Agenda for Studying Credibility Perceptions of Visual Misinformation. Political Communication, 40(2), 225-237. https://doi.org/10.1080/10584609.2023.2175398 DOI: https://doi.org/10.1080/10584609.2023.2175398
Pulm, C., Gast, A., & Rummel, J. (2024). A Picture Corrects a Thousand Words – The Effect of Photos on Veracity Feedback. Consciousness and Cognition, 125, 103758. https://doi.org/10.1016/j.concog.2024.103758 DOI: https://doi.org/10.1016/j.concog.2024.103758
Qian, S., Shen, C., & Zhang, J. (2022). Fighting cheapfakes: Using a digital media literacy intervention to motivate reverse search of out-of-context visual misinformation. Journal of Computer-Mediated Communication, 28(1), zmac024. https://doi.org/10.1093/jcmc/zmac024 DOI: https://doi.org/10.1093/jcmc/zmac024
Rauchfleisch, A., Vogler, D., & De Seta, G. (2025). Deepfakes or Synthetic Media? The Effect of Euphemisms for Labeling Technology on Risk and Benefit Perceptions. Social Media + Society, 11(3), 20563051251350975. https://doi.org/10.1177/20563051251350975 DOI: https://doi.org/10.1177/20563051251350975
Ross Arguedas, A. A., Badrinathan, S., Mont’Alverne, C., Toff, B., Fletcher, R., & Nielsen, R. K. (2024). Shortcuts to trust: Relying on cues to judge online news from unfamiliar sources on digital platforms. Journalism, 25(6), 1207-1229. https://doi.org/10.1177/14648849231194485 DOI: https://doi.org/10.1177/14648849231194485
Schiff, K. J., Schiff, D. S., & Bueno, N. S. (2025). The Liar’s Dividend: Can Politicians Claim Misinformation to Evade Accountability? American Political Science Review, 119(1), 71-90. https://doi.org/10.1017/S0003055423001454 DOI: https://doi.org/10.1017/S0003055423001454
Shen, M., Luo, Z., & Liao, Y. (2024). Comprehensive Out-of-context Misinformation Detection via Global Information Enhancement. Proceedings of the 2024 2nd International Conference on Advances in Artificial Intelligence and Applications, 138-142. https://doi.org/10.1145/3712623.3712660 DOI: https://doi.org/10.1145/3712623.3712660
Steensen, S., Kalsnes, B., & Westlund, O. (2024). The limits of live fact-checking: Epistemological consequences of introducing a breaking news logic to political fact-checking. New Media & Society, 26(11), 6347-6365. https://doi.org/10.1177/14614448231151436 DOI: https://doi.org/10.1177/14614448231151436
Suomalainen, K., Nykänen, N., Seeck, H., Kim, Y., & McPherson, E. (2025). Fact-Checking in Journalism: An Epistemological Framework. Journalism Studies, 26(10), 1129-1149. https://doi.org/10.1080/1461670X.2025.2492729 DOI: https://doi.org/10.1080/1461670X.2025.2492729
Ternovski, J., Kalla, J., & Aronow, P. (2022). Negative Consequences of Informing Voters about Deepfakes: Evidence from Two Survey Experiments. Journal of Online Trust and Safety, 1(2). https://doi.org/10.54501/jots.v1i2.28 DOI: https://doi.org/10.54501/jots.v1i2.28
Tonglet, J., Thiem, G., & Gurevych, I. (2025). COVE: COntext and VEracity prediction for out-of-context images. Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2029-2049. https://doi.org/10.18653/v1/2025.naacl-long.102 DOI: https://doi.org/10.18653/v1/2025.naacl-long.102
Vaccari, C., & Chadwick, A. (2020). Deepfakes and Disinformation: Exploring the Impact of Synthetic Political Video on Deception, Uncertainty, and Trust in News. Social Media + Society, 6(1), 2056305120903408. https://doi.org/10.1177/2056305120903408 DOI: https://doi.org/10.1177/2056305120903408
Vinhas, O., & Bastos, M. (2022). Fact-Checking Misinformation: Eight Notes on Consensus Reality. Journalism Studies, 23(4), 448-468. https://doi.org/10.1080/1461670X.2022.2031259 DOI: https://doi.org/10.1080/1461670X.2022.2031259
Vinhas, O., & Bastos, M. (2025). The WEIRD governance of fact-checking and the politics of content moderation. New Media & Society, 27(5), 2768-2787. https://doi.org/10.1177/14614448231213942 DOI: https://doi.org/10.1177/14614448231213942
Weikmann, T., & Lecheler, S. (2023). Visual disinformation in a digital age: A literature synthesis and research agenda. New Media & Society, 25(12), 3696-3713. https://doi.org/10.1177/14614448221141648 DOI: https://doi.org/10.1177/14614448221141648
Weikmann, T., & Lecheler, S. (2024). Cutting through the Hype: Understanding the Implications of Deepfakes for the Fact-Checking Actor-Network. Digital Journalism, 12(10), 1505-1522. https://doi.org/10.1080/21670811.2023.2194665 DOI: https://doi.org/10.1080/21670811.2023.2194665
Westlund, O., Belair-Gagnon, V., Graves, L., Larsen, R., & Steensen, S. (2024). What Is the Problem with Misinformation? Fact-checking as a Sociotechnical and Problem-Solving Practice. Journalism Studies, 25(8), 898-918. https://doi.org/10.1080/1461670X.2024.2357316 DOI: https://doi.org/10.1080/1461670X.2024.2357316
Wilson, A., Wilkes, S., Teramoto, Y., & Hale, S. (2023). Multimodal analysis of disinformation and misinformation. Royal Society Open Science, 10(12), 230964. https://doi.org/10.1098/rsos.230964 DOI: https://doi.org/10.1098/rsos.230964
Wittenberg, C., Epstein, Z., Péloquin-Skulski, G., Berinsky, A. J., & Rand, D. G. (2025). Labeling AI-generated media online. PNAS Nexus, 4(6), pgaf170. https://doi.org/10.1093/pnasnexus/pgaf170 DOI: https://doi.org/10.1093/pnasnexus/pgaf170
Zeng, J., & Brennen, S. B. (2023). Misinformation. Internet Policy Review, 12(4). https://doi.org/10.14763/2023.4.1725 DOI: https://doi.org/10.14763/2023.4.1725
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Authors retain copyright and transfer to the journal the right of first publication and publishing rights
This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License.
Those authors who publish in this journal accept the following terms:
-
Authors retain copyright.
-
Authors transfer to the journal the right of first publication. The journal also owns the publishing rights.
-
All published contents are governed by an Attribution-NoDerivatives 4.0 International License.
Access the informative version and legal text of the license. By virtue of this, third parties are allowed to use what is published as long as they mention the authorship of the work and the first publication in this journal. If you transform the material, you may not distribute the modified work. -
Authors may make other independent and additional contractual arrangements for non-exclusive distribution of the version of the article published in this journal (e.g., inclusion in an institutional repository or publication in a book) as long as they clearly indicate that the work was first published in this journal.
- Authors are allowed and recommended to publish their work on the Internet (for example on institutional and personal websites), following the publication of, and referencing the journal, as this could lead to constructive exchanges and a more extensive and quick circulation of published works (see The Effect of Open Access).
