Abstract

While concerns about the risks of AI-generated content (AIGC) to the integrity of social media discussions have been raised, little is known about its scale and the actors responsible for its dissemination online. In this work, we identify and characterize the prevalence, sharing patterns, and spreaders of AIGC in different modalities, including images and texts. Analyzing a large-scale dataset from X related to the 2024 U.S. Presidential Election, we find that approximately 12% of images and 1.4% of texts are deemed AI-generated. Notably, roughly 3% of text spreaders and 10% of image spreaders account for 80% of the AI-generated content within their respective modalities. Superspreaders of AIGC are more likely to be X Premium subscribers with a right-leaning orientation and exhibit automated behavior. Additionally, AI image spreaders have a higher proportion of AI-generated content in their profiles compared to AI text spreaders. This study serves as a very first step toward understanding the role generative AI plays in shaping online socio-political environments and offers implications for platform governance.

Metadata

publication

arXiv preprint arXiv:2502.11248, 2025

year

2025

publication date

2025/2/16

authors

Zhiyi Chen, Jinyi Ye, Emilio Ferrara, Luca Luceri

link

https://arxiv.org/abs/2502.11248

resource_link

https://arxiv.org/pdf/2502.11248

journal

arXiv preprint arXiv:2502.11248