# Machines in the Crowd? Measuring the Footprint of Machine-Generated Text on Reddit arXiv: https://arxiv.org/abs/2510.07226 ยท HTML: https://mlsanity.com/paper/2510.07226/ ## Key facts - Cited by 4 papers in the map (data through 14 Oct 2026). - Builds on 30 of its 48 references that are in the map. - First posted on arXiv 8 Oct 2025. ## Builds on (most cited first, 30 of 30) - [DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability Curvature](https://mlsanity.com/paper/2301.11305/) (2023) - [GLTR: Statistical Detection and Visualization of Generated Text](https://mlsanity.com/paper/1906.04043/) (2019) - [How Close is ChatGPT to Human Experts? Comparison Corpus, Evaluation, and Detection](https://mlsanity.com/paper/2301.07597/) (2023) - [The Pushshift Reddit Dataset](https://mlsanity.com/paper/2001.08435/) (2020) - [Fast-DetectGPT: Efficient Zero-Shot Detection of Machine-Generated Text via Conditional Probability Curvature](https://mlsanity.com/paper/2310.05130/) (2023) - [Spotting LLMs With Binoculars: Zero-Shot Detection of Machine-Generated Text](https://mlsanity.com/paper/2401.12070/) (2024) - [DetectLLM: Leveraging Log Rank Information for Zero-Shot Detection of Machine-Generated Text](https://mlsanity.com/paper/2306.05540/) (2023) - [Generative artificial intelligence enhances creativity but reduces the diversity of novel content](https://mlsanity.com/paper/2312.00506/) (2023) - [Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviews](https://mlsanity.com/paper/2403.07183/) (2024) - [Emergent social conventions and collective bias in LLM populations](https://mlsanity.com/paper/2410.08948/) (2024) - [MGTBench: Benchmarking Machine-Generated Text Detection](https://mlsanity.com/paper/2303.14822/) (2023) - [Artificial Intelligence in the Creative Industries: A Review](https://mlsanity.com/paper/2007.12391/) (2020) - [AI Suggestions Homogenize Writing Toward Western Styles and Diminish Cultural Nuances](https://mlsanity.com/paper/2409.11360/) (2024) - [Stylometric Detection of AI-Generated Text in Twitter Timelines](https://mlsanity.com/paper/2303.03697/) (2023) - [DeTeCtive: Detecting AI-generated Text via Multi-Level Contrastive Learning](https://mlsanity.com/paper/2410.20964/) (2024) - [The Persuasive Power of Large Language Models](https://mlsanity.com/paper/2312.15523/) (2023) - [Machine-Made Media: Monitoring the Mobilization of Machine-Generated Articles on Misinformation and Mainstream News Websites](https://mlsanity.com/paper/2305.09820/) (2023) - [Are We in the AI-Generated Text World Already? Quantifying and Monitoring AIGT on Social Media](https://mlsanity.com/paper/2412.18148/) (2024) - [How malicious AI swarms can threaten democracy: The fusion of agentic AI and LLMs marks a new frontier in information warfare](https://mlsanity.com/paper/2506.06299/) (2025) - [Ten Social Dimensions of Conversations and Relationships](https://mlsanity.com/paper/2001.09954/) (2020) - [What Makes Online Communities 'Better'? Measuring Values, Consensus, and Conflict across Thousands of Subreddits](https://mlsanity.com/paper/2111.05835/) (2021) - [The language of opinion change on social media under the lens of communicative action](https://mlsanity.com/paper/2210.17234/) (2022) - [Advancing the Search Frontier with AI Agents](https://mlsanity.com/paper/2311.01235/) (2023) - [Is Contrasting All You Need? Contrastive Learning for the Detection and Attribution of AI-generated Text](https://mlsanity.com/paper/2407.09364/) (2024) - [OpenTuringBench: An Open-Model-based Benchmark and Framework for Machine-Generated Text Detection and Attribution](https://mlsanity.com/paper/2504.11369/) (2025) - [Examining the Prevalence and Dynamics of AI-Generated Media in Art Subreddits](https://mlsanity.com/paper/2410.07302/) (2024) - [Exposing Cross-Platform Coordinated Inauthentic Activity in the Run-Up to the 2024 U.S. Election](https://mlsanity.com/paper/2410.22716/) (2024) - [AI Rules? Characterizing Reddit Community Policies Towards AI-Generated Content](https://mlsanity.com/paper/2410.11698/) (2024) - [Coloring in the Links: Capturing Social Ties as They are Perceived](https://mlsanity.com/paper/1902.04528/) (2019) - [Causal Modeling of Climate Activism on Reddit](https://mlsanity.com/paper/2410.10562/) (2024) ## Built on by (most cited first, 4 of 4) - [On the Detectability of LLM-Generated Text: What Exactly Is LLM-Generated Text?](https://mlsanity.com/paper/2510.20810/) (2025) - [How AI Writing Assistance Distorts Perceptions of AI Users and Their Opinions](https://mlsanity.com/paper/2604.22503/) (2026) - [Luminol-AIDetect: Fast Zero-shot Machine-Generated Text Detection based on Perplexity under Text Shuffling](https://mlsanity.com/paper/2604.25860/) (2026) - [DeGenTWeb: A First Look at LLM-dominant Websites](https://mlsanity.com/paper/2605.00087/) (2026) ## Abstract (arXiv) 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.