Generative Memesis: AI Mediates Political Memes in the 2024 USA Presidential Election
Ho-Chun Herbert Chang, Benjamin Shaman, Yung-chun Chen, Mingyue Zha,, Sean Noh, Chiyu Wei, Tracy Weener, Maya Magee

TL;DR
This study analyzes how AI-generated political memes influence social media engagement during the 2024 US presidential election, revealing partisan differences and the emergence of AI-mediated meme creation.
Contribution
It introduces the concept of generative memesis, showing how AI mediates political meme sharing and highlighting partisan divergences in meme usage.
Findings
Synthetic content mediates political information creation.
Partisan differences in AI meme usage: Democrats support, Republicans attack.
Non-traditional outlets are primary meme creators.
Abstract
Visual content on social media has become increasingly influential in shaping political discourse and civic engagement. Using a dataset of 239,526 Instagram images, deep learning, and LLM-based workflows, we examine the impact of different content types on user engagement during the 2024 US presidential Elections, with a focus on synthetic visuals. Results show while synthetic content may not increase engagement alone, it mediates how political information is created through highly effective, often absurd, political memes. We define the notion of generative memesis, where memes are no longer shared person-to-person but mediated by AI through customized, generated images. We also find partisan divergences: Democrats use AI for in-group support whereas Republicans use it for out-group attacks. Non-traditional, left-leaning outlets are the primary creators of political memes; emphasis on…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsLanguage, Metaphor, and Cognition · Humor Studies and Applications · Digital Communication and Language
MethodsFocus
