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    <abstract>Argumentation is, at its core, an inherently verbal activity. Yet, other modalities may support arguments, one of which are images. In the argument mining community, this combination has not received much attention yet. While a few previous works studied whether images can make argumentative texts more effective in persuading people, the images that were considered matched the texts loosely only, or they were heavily text-based themselves. In this paper, we take the step to study to what extent the persuasive effect of textual arguments can be supported by images specifically created for this purpose. For a consistent experiment design, we combine NLP with image generation to synthesize both arguments and images with generative AI, for five controversial topics and for two rhetorical strategies. In two consecutive user studies, we first determine the best-matching image for each argument and then compare the perceived effect of bare textual arguments to those that are supported by an image. Our results suggest that the images may increase the persuasive effect of argumentative texts, but with variance across topics.</abstract>
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%0 Conference Proceedings
%T Assessing the Persuasive Effect of AI-Generated Image Support of Arguments
%A Quadras, Mackwyn
%A Stede, Manfred
%A Wachsmuth, Henning
%Y Piperidis, Stelios
%Y Bel, Núria
%Y van den Heuvel, Henk
%Y Ide, Nancy
%Y Krek, Simon
%Y Toral, Antonio
%S Proceedings of the Fifteenth Language Resources and Evaluation Conference
%D 2026
%8 May
%I ELRA Language Resource Association
%C Palma de Mallorca, Spain
%F quadras-etal-2026-assessing
%X Argumentation is, at its core, an inherently verbal activity. Yet, other modalities may support arguments, one of which are images. In the argument mining community, this combination has not received much attention yet. While a few previous works studied whether images can make argumentative texts more effective in persuading people, the images that were considered matched the texts loosely only, or they were heavily text-based themselves. In this paper, we take the step to study to what extent the persuasive effect of textual arguments can be supported by images specifically created for this purpose. For a consistent experiment design, we combine NLP with image generation to synthesize both arguments and images with generative AI, for five controversial topics and for two rhetorical strategies. In two consecutive user studies, we first determine the best-matching image for each argument and then compare the perceived effect of bare textual arguments to those that are supported by an image. Our results suggest that the images may increase the persuasive effect of argumentative texts, but with variance across topics.
%R 10.63317/2b6xxx7vmyra
%U https://aclanthology.org/2026.lrec-1.641/
%U https://doi.org/10.63317/2b6xxx7vmyra
%P 8085-8095

Markdown (Informal)

[Assessing the Persuasive Effect of AI-Generated Image Support of Arguments](https://aclanthology.org/2026.lrec-1.641/) (Quadras et al., LREC 2026)

• Assessing the Persuasive Effect of AI-Generated Image Support of Arguments (Quadras et al., LREC 2026)

ACL

• Mackwyn Quadras, Manfred Stede, and Henning Wachsmuth. 2026. Assessing the Persuasive Effect of AI-Generated Image Support of Arguments. In Proceedings of the Fifteenth Language Resources and Evaluation Conference, pages 8085–8095, Palma de Mallorca, Spain. ELRA Language Resource Association.