Machines in the Crowd? Measuring the Footprint of Machine-Generated Text on Reddit

Lucio La Cava, Luca Maria Aiello, Andrea Tagarelli
10/8/2025
cs.SIcs.CLcs.CY

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Abstract

Generative Artificial Intelligence is reshaping online communication by enabling large-scale production of Machine-Generated Text (MGT) at low cost. While its presence is rapidly growing across the Web, little is known about how MGT integrates into social media environments. In this paper, we present the first large-scale characterization of MGT on Reddit. Using a state-of-the-art statistical method for detection of MGT, we analyze over two years of activity (2022-2024) across 51 subreddits representative of Reddit's main community types such as information seeking, social support, and discussion. We study the concentration of MGT across communities and over time, and compared MGT to human-authored text in terms of social signals it expresses and engagement it receives. Our very conservative estimate of MGT prevalence indicates that synthetic text is marginally present on Reddit, but it can reach peaks of up to 9% in some communities in some months. MGT is unevenly distributed across communities, more prevalent in subreddits focused on technical knowledge and social support, and often concentrated in the activity of a small fraction of users. MGT also conveys distinct social signals of warmth and status giving typical of language of AI assistants. Despite these stylistic differences, MGT achieves engagement levels comparable than human-authored content and in a few cases even higher, suggesting that AI-generated text is becoming an organic component of online social discourse. This work offers the first perspective on the MGT footprint on Reddit, paving the way for new investigations involving platform governance, detection strategies, and community dynamics.

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@article{cava2025machines,
  title  = {Machines in the Crowd? Measuring the Footprint of Machine-Generated Text on Reddit},
  author = {Lucio La Cava and Luca Maria Aiello and Andrea Tagarelli},
  year   = {2025},
  eprint = {2510.07226},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2510.07226v1}
}

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