Generative Memesis: AI Mediates Political Memes in the 2024 USA Presidential Election

• URL: http://arxiv.org/abs/2411.00934v1
• Date: Fri, 01 Nov 2024 17:35:05 GMT
• Title: Generative Memesis: AI Mediates Political Memes in the 2024 USA Presidential Election
• Authors: Ho-Chun Herbert Chang, Benjamin Shaman, Yung-chun Chen, Mingyue Zha, Sean Noh, Chiyu Wei, Tracy Weener, Maya Magee,
• Abstract summary: Using a dataset of 239,526 Instagram images, we examine the impact of different content types on user engagement during the 2024 US presidential Elections. Results show while synthetic content may not increase engagement alone, it mediates how political information is created through highly effective, often absurd, political memes.
• Score: 1.4304078520604593
• License:
• 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 different topics largely follows issue ownership.

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