A new face of political advertising? Synthetic imagery in the 2025 German federal election campaigns on social media

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Cover of Volume: SCM Studies in Communication and Media Volume 14 (2025), Edition 4
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SCM Studies in Communication and Media

Volume 14 (2025), Edition 4

Authors:
Publisher
Nomos, Baden-Baden
Copyright year
2026
ISSN-Online
2192-4007
ISSN-Print
2192-4007

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Open Access Full access

Volume 14 (2025), Edition 4

A new face of political advertising? Synthetic imagery in the 2025 German federal election campaigns on social media

Authors:
ISSN-Print
2192-4007
ISSN-Online
2192-4007
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The rise of AI-generated content represents a new frontier in political communication. As synthetic media become more sophisticated and accessible, their role in shaping voter perceptions and influencing public discourse warrants closer examination. This study examines the use of AI-generated images in the 2025 German federal election campaign, assessing their prevalence, strategic use, and transparency. We conducted a content analysis of Instagram posts from the major German political parties and their youth organizations in the six weeks leading up to the election. Our analysis focused on identifying AI-generated visuals, evaluating their labeling practices, and examining their communicative and ideological functions. We also compared differences in adoption and usage patterns across parties to assess potential implications for democratic processes. Our findings indicate that the far-right Alternative for Germany (AfD) uses synthetic visuals significantly more than other parties. These AI-generated images are predominantly photorealistic and often lack clear labeling, raising concerns about transparency and potential voter deception. The AfD primarily uses such visuals for emotional and ideological messaging, using AI-generated content to reinforce its political narratives and mobilize support. Our findings provide a structured assessment of AI-generated content in German political communication and highlight the potential risks associated with unregulated use of synthetic media in electoral campaigns. Our research also contributes to the broader discourse on the ethical implications of synthetic media in democratic societies.

Bibliography

  1. Bast, J. (2024). Managing the image. The visual communication strategy of European right-wing populist politicians on Instagram. Journal of Political Marketing, 23(1), 1–25. ­https://doi.org/10.1080/15377857.2021.1892901 Open Google Scholar
  2. Bennett, W. L., & Livingston, S. (2018). The disinformation order: Disruptive communication and the decline of democratic institutions. European Journal of Communication, 33(2), 122–139. https://doi.org/10.1177/0267323118760317 Open Google Scholar
  3. Bray, S. D., Johnson, S. D., & Kleinberg, B. (2023). Testing human ability to detect ‘deepfake’ images of human faces. Journal of Cybersecurity, 9(1), 1–18. https://doi.org/10.1093/ Open Google Scholar
  4. cybsec/tyad011 Open Google Scholar
  5. Brettschneider, F., Niedermayer, O., & Weßels, B. (2007). Die Bundestagswahl 2005: Analysen des Wahlkampfes und der Wahlergebnisse [The German federal election 2005: Analyses of the election campaign and results]. In: F. Brettschneider, O. Niedermayer, B. Weßels (Eds.), Die Bundestagswahl 2005 (pp. 9–18). VS https://doi.org/10.1007/978-3-531-90536-5_1 Open Google Scholar
  6. Burrus, O., Curtis, A., & Herman, L. (2024). Unmasking AI: Informing authenticity decisions by labeling AI-generated content. Interactions, 31(4), 38–42. https://doi.org/10.1145/3665321 Open Google Scholar
  7. Campbell, A. (1960). Surge and decline: A study of electoral change. Public Opinion Quarterly, 24(3), 397–418. https://psycnet.apa.org/doi/10.1086/266960 Open Google Scholar
  8. Corsi, G., Marino, B., & Wong, W. (2024). The spread of synthetic media on X. Harvard Kennedy School (HKS) Misinformation Review. https://doi.org/10.37016/mr-2020-140 Open Google Scholar
  9. Dalton, R. J. (2018). Citizen politics: Public opinion and political parties in advanced industrial democracies. CQ Press. Open Google Scholar
  10. De Vreese, C. D., & Votta, F. (2023). AI and political communication. Political Communication Report, 2023. http://doi.org/10.17169/refubium-39047 Open Google Scholar
  11. Dobber, T., Metoui, N., Trilling, D., Helberger, N., & De Vreese, C. (2021). Do (microtargeted) deepfakes have real effects on political attitudes? The International Journal of Press/Politics, 26(1), 69–91. https://doi.org/10.1177/1940161220944364 Open Google Scholar
  12. Engesser, S., Ernst, N., Esser, F., & Büchel, F. (2017). Populism and social media: How politicians spread a fragmented ideology. Information, Communication & Society, 20(8), 1109–1126. https://doi.org/10.1080/1369118X.2016.1207697 Open Google Scholar
  13. Ernst, N., Blassnig, S., Engesser, S., Büchel, F., & Esser, F. (2019). Populists prefer social media over talk shows: An analysis of populist messages and stylistic elements across six countries. Social Media+ Society, 5(1). https://doi.org/10.1177/2056305118823358 Open Google Scholar
  14. Epstein, Z., Arechar, A. A., & Rand, D. (2023). What label should be applied to content produced by generative AI? PsyArxiv preprint, 2023. https://doi.org/10.31234/osf.io/v4mfz Open Google Scholar
  15. Esser, F., & Strömbäck, J. (2014). Mediatization of politics: Understanding the transformation of Western democracies. Springer. https://doi.org/10.1057/9781137275844 Open Google Scholar
  16. Farrell, D.M., & Schmitt-Beck, R. (Eds.). (2002). Do political campaigns matter? Campaign Effects in Elections and Referendums (1st ed.). Routledge. https://doi.org/10.4324/9780203166956 Open Google Scholar
  17. Geise, S., & Baden, C. (2015). Putting the image back into the frame: Modeling the linkage between visual communication and frame-processing theory. Communication Theory, 25(1), 46–69. https://doi.org/10.1111/comt.12048 Open Google Scholar
  18. Geise, S., & Xu, Y. (2024). Effects of visual framing in multimodal media environments: A systematic review of studies between 1979 and 2023. Journalism & Mass Communication Quarterly, 102(3), 796–823. https://doi.org/10.1177/10776990241257586 Open Google Scholar
  19. Gerbaudo, P. (2018). Social media and populism: an elective affinity? Media, Culture & Society, 40(5), 745–753. https://doi.org/10.1177/0163443718772192 Open Google Scholar
  20. Gibson, R. K., & McAllister, I. (2015). Normalising or equalising party competition? Assessing the impact of the web on election campaigning. Political Studies, 63(3), 529–547. ­https://doi.org/10.1111/1467-9248.12107 Open Google Scholar
  21. Godulla, A., Hoffmann, C. P., & Seibert, D. (2021). Dealing with deepfakes–An interdisciplinary examination of the state of research and implications for communication studies. SCM Studies in Communication and Media, 10(1), 72–96. https://doi.org/10.5771/2192-4007-2021-1-72 Open Google Scholar
  22. Gosselin, R. D. (2025). AI detectors are poor western blot classifiers: A study of accuracy and predictive values. PeerJ, 13. https://doi.org/10.7717/peerj.18988 Open Google Scholar
  23. Grabe, M. E., & Bucy, E. P. (2009). Image bite politics: News and the visual framing of elections. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780195372076.001.0001 Open Google Scholar
  24. Graf & Koch-Kramer (2020) Instaloader. Retrieved January 10, 2025, from https://github.com/instaloader/instaloader. Open Google Scholar
  25. Grittmann, E. (2007). Das politische Bild: Fotojournalismus und Pressefotografie in Theorie und Empirie [The political image: Photojournalism and press photography in theory and empirical research]. Herbert von Halem. Open Google Scholar
  26. Habermas, J. (1983). Moralbewußtsein und kommunikatives Handeln [Moral consciousness and communicative action]. Suhrkamp. Open Google Scholar
  27. 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, 6291–6311. Open Google Scholar
  28. Hameleers, M., & Schmuck, D. (2017). It’s us against them: A comparative experiment on the effects of populist messages communicated via social media. Information, Communication & Society, 20(9), 1425–1444. https://doi.org/10.1080/1369118X.2017.1328523 Open Google Scholar
  29. Hameleers, M., van der Meer, T. G., & Dobber, T. (2024). Distorting the truth versus blatant lies: The effects of different degrees of deception in domestic and foreign political deepfakes. Computers in Human Behavior, 152. https://doi.org/10.1016/j.chb.2023.108096 Open Google Scholar
  30. Hausken, L. (2024). Photorealism versus photography. AI-generated depiction in the age of visual disinformation. Journal of Aesthetics & Culture, 16(1). https://doi.org/10.1080/20004214.2024.2340787 Open Google Scholar
  31. Hooghe, M., Stolle, D., & Stouthuysen, P. (2004). Head start in politics: The recruitment function of youth organizations of political parties in Belgium (Flanders). Party Politics, 10(2), 193–212. https://doi.org/10.1177/1354068804040503 Open Google Scholar
  32. Klinger, U., Koc-Michalska, K., & Russmann, U. (2023). Are campaigns getting uglier, and who is to blame? Negativity, dramatization and populism on Facebook in the 2014 and 2019 EP election campaigns. Political Communication, 40(3), 263–282. https://doi.org/10.1080/10584609.2022.2133198 Open Google Scholar
  33. Laba, N. (2024). Engine for the imagination? Visual generative media and the issue of ­representation. Media, Culture & Society, 46(8), 1599–1620. https://doi.org/10.1177/01634437241259950 Open Google Scholar
  34. Leidecker-Sandmann, M., & Geise, S. (2020). Tradition statt Innovation. Die deutsche Presseberichterstattung über die Wahlkampfstrategien der Parteien zur Bundestagswahl 2017 [Tradition instead of innovation. The German press coverage of political parties’ campaign­ strategies in the run-up to the 2017 parliamentary elections]. SCM Studies in Communication and Media, 9(2), 264–307. https://doi.org/10.5771/2192-4007-2020-2-264 Open Google Scholar
  35. Leidecker-Sandmann, M., & Thomas, F. (2023). “Never was there more to do.” Use of vaguely formulated statements in the 2021 German national election campaign and their potential effects. In C. Holtz-Bacha, (Ed.), Die (Massen-)Medien im Wahlkampf: Die Bundestagswahl 2021 (pp. 43–66). Springer Fachmedien Wiesbaden. Open Google Scholar
  36. Li, Y., Liu, Z., Zhao, J., Ren, L., Li, F., Luo, J., & Luo, B. (2024). The adversarial AI-art: Understanding, generation, detection, and benchmarking. In European Symposium on Research in Computer Security (pp. 311–331). Springer Nature Switzerland. https://doi.org/10.48550/arXiv.2404.14581 Open Google Scholar
  37. Lu, Z., Huang, D., Bai, L., Qu, J., Wu, C., Liu, X., & Ouyang, W. (2023). Seeing is not always believing: Benchmarking human and model perception of AI-generated images. Advances in Neural Information Processing Systems, 36, 25435–25447. https://doi.org/10.48550/arXiv.2304.13023 Open Google Scholar
  38. Mathys, M., Willi, M., & Meier, R. (2024). Synthetic photography detection: A visual guidance for identifying synthetic images created by AI. arXiv preprint arXiv:2408.06398. https://doi.org/10.48550/arXiv.2408.06398 Open Google Scholar
  39. Magin, M., Podschuweit, N., Haßler, J., & Russmann, U. (2017). Campaigning in the fourth age of political communication. A multi-method study on the use of Facebook by German and Austrian parties in the 2013 national election campaigns. Information, Communication & Society, 20(11), 1698–1719. https://doi.org/10.1080/1369118X.2016.1254269 Open Google Scholar
  40. Messaris, P., & Abraham, L. (2001). The role of images in framing news stories. In S. D. Reese, O. H. Gandy, Jr., & A. E. Grant (Eds.), Framing public life: Perspectives on media and our understanding of the social world (pp. 231–242). Routledge. Open Google Scholar
  41. Moernaut, R., Mast, J., & Pauwels, L. (2020). Visual and multimodal framing analysis. In L. Pauwels, D. Mannay (Eds.), The SAGE Handbook of Visual Research Methods (pp. 484–499). SAGE Publications. https://doi.org/10.4135/9781526417015.n30 Open Google Scholar
  42. Momeni, M. (2025). Artificial intelligence and political deepfakes: Shaping citizen perceptions through misinformation. Journal of Creative Communications, 20(1), 41–56. https://doi.org/10.1177/09732586241277335 Open Google Scholar
  43. Müller, M. G. (1997). Visuelle Wahlkampfkommunikation: Eine Typologie der Bildstrategien im amerikanischen Präsidentschaftswahlkampf [Visual campaign communication: A typology of image strategies in the American presidential election campaign]. Publizistik, 42(2), 205–228. https://doi.org/10.1007/BF03654575 Open Google Scholar
  44. Perloff, R. M. (2021). The dynamics of political communication: Media and politics in a digital age. Routledge. https://doi.org/10.4324/9780429298851 Open Google Scholar
  45. Powell, T. E., Boomgaarden, H. G., De Swert, K., & de Vreese, C. H. (2019). Framing fast and slow: A dual processing account of multimodal framing effects. Media Psychology, 22(4), 572–600. https://doi.org/10.1080/15213269.2018.1476891 Open Google Scholar
  46. Peng, Q., Lu, Y., Peng, Y., Qian, S., Liu, X., & Shen, C. (2025, April). Crafting synthetic realities: Examining visual realism and misinformation potential of photorealistic AI-generated images. In Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (pp. 1–12). https://doi.org/10.1145/3706599.3719834 Open Google Scholar
  47. Schmuck, D., & Matthes, J. (2017). Effects of economic and symbolic threat appeals in right-wing populist advertising on anti-immigrant attitudes: The impact of textual and visual appeals. Political Communication, 34(4), 607–626. https://doi.org/10.1080/10584609.2017.1316807 Open Google Scholar
  48. Semetko, H. A., & Tworzecki, H. (2017). Campaign strategies, media, and voters: The fourth era of political communication. In J. Fisher, E. Fieldhouse, M.N. Franklin, R. Gibson, M. Cantijoch & C. Wlezien (Eds.), The Routledge Handbook of Elections, Voting Behavior and Public Opinion (pp. 293–304). Routledge. Open Google Scholar
  49. Seo, K. (2020). Meta-analysis on visual persuasion–does adding images to texts influence persuasion? Athens Journal of Mass Media and Communications, 6(3), 177–190. https://doi.org/10.30958/ajmmc.6-3-3 Open Google Scholar
  50. Ternovski, J., Kalla, J., & Aronow, P. (2022). The 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 Open Google Scholar
  51. 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 Open Google Scholar
  52. Ward, J. (2011). Reaching citizens online: How youth organizations are evolving their web presence. Information, Communication & Society, 14(6), 917–936. https://doi.org/10.1080/1369118X.2011.572982 Open Google Scholar
  53. Weber, R. (2017). Political participation of young people in political parties. Zeitschrift für Politikwissenschaft, 27, 379–396. https://doi.org/10.1007/s41358-017-0106-z Open Google Scholar
  54. Wilke, J., & Leidecker, M. (2013). Regional – national – supranational. How the German press covers election campaigns on different levels of the political system. Central European Journal of Communication, 6(1(10)), 122–143 Open Google Scholar
  55. Wilke, J., & Reinemann, C. (2003). Die Bundestagswahl 2002: Ein Sonderfall? [The German federal election 2002: A special case?]. In: C. Holtz-Bacha, C. (Eds.), Die Massenmedien im Wahlkampf (pp. 29–46). VS. https://doi.org/10.1007/978-3-322-80461-7_3 Open Google Scholar
  56. Wittenberg, C., Epstein, Z., Berkinsky, A.J., & Rand, D.G. (2023). Labeling AI-generated content: Promises, perils, and future directions. Topical Policy Brief, MIT Schwarzman College of Computing. https://computing.mit.edu/wp-content/uploads/2023/11/AI-Policy_Labeling.pdf Open Google Scholar

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