Visual content on social media has become increasingly influential in shaping political discourse and civic engagement, but it also limits participation due to the increased cost of multimedia production. In tandem, the growth of generative AI provides novel ways for citizens to participate in politics by lowering these costs. Drawing on a dataset of 239,526 Instagram images, we analyze the effects of synthetic images during the 2024 United States presidential election, using a multimodal workflow combining computer vision, large language models, and facial affect analysis. Results show that meme format is a stronger predictor of engagement than AI-generated content alone. However, AI-generated memes yield a significant interaction effect, suggesting synergistic increases in engagement when synthetic imagery is integrated with memes through human curation. We also characterize how users curate images. Partisans use AI in different ways: Democrat-leaning users tend to use it for in-group support, whereas Republican-leaning users more often employ it for out-group attacks. Users generally select happier synthetic faces compared to real photographs. We define generative memesis as a mode of communication in which memes are no longer shared person-to-person, but mediated by AI through customized visuals. We discuss how generative AI may empower civic participation, the bifurcation of content production and curation, and its implications for in the history of novel technologies and participatory culture.

翻译：社交媒体上的视觉内容在塑造政治话语和公民参与方面日益具有影响力，但也因多媒体制作成本上升而限制了参与度。与此同时，生成式人工智能的发展通过降低这些成本，为公民参与政治提供了新途径。基于239,526张Instagram图像数据集，我们采用结合计算机视觉、大型语言模型和面部情感分析的多模态方法，分析了合成图像在2024年美国总统大选期间的效应。结果显示，迷因形式比单纯AI生成内容更能预测参与度。然而，AI生成的迷因呈现出显著的交互效应，表明当合成图像通过人工策展与迷因结合时，参与度会产生协同增长。我们还揭示了用户如何策展图像：不同党派用户以不同方式使用AI——倾向民主党的用户多将其用于本群体支持，而倾向共和党的用户则更常用于攻击外群体。与真实照片相比，用户普遍选择面部表情更愉悦的合成图像。我们将生成式模因定义为一种新型传播模式：迷因不再通过人与人直接分享，而是通过AI以定制化视觉媒介进行传输。我们探讨了生成式AI可能如何赋能公民参与、内容生产与策展的分化现象，及其在新技术史与参与式文化背景下的深远影响。