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As large language models (LLMs) like ChatGPT have gained traction, anincreasing number of news websites have begun utilizing them to generatearticles. However, not only can these language models produce factuallyinaccurate articles on reputable websites but disreputable news sites canutilize LLMs to mass produce misinformation. To begin to understand thisphenomenon, we present one of the first large-scale studies of the prevalenceof synthetic articles within online news media. To do this, we train aDeBERTa-based synthetic news detector and classify over 15.90 million articlesfrom 3,074 misinformation and mainstream news websites. We find that betweenJanuary 1, 2022, and May 1, 2023, the relative number of synthetic newsarticles increased by 55.4% on mainstream websites while increasing by 457% onmisinformation sites. We find that this increase is largely driven by smallerless popular websites. Analyzing the impact of the release of ChatGPT using aninterrupted-time-series, we show that while its release resulted in a markedincrease in synthetic articles on small sites as well as misinformation newswebsites, there was not a corresponding increase on large mainstream newswebsites.

Machine-Made Media: Monitoring the Mobilization of Machine-Generated Articles on Misinformation and Mainstream News Websites