As large language models (LLMs) like ChatGPT have gained traction, an increasing number of news websites have begun utilizing them to generate articles. However, not only can these language models produce factually inaccurate articles on reputable websites but disreputable news sites can utilize LLMs to mass produce misinformation. To begin to understand this phenomenon, we present one of the first large-scale studies of the prevalence of synthetic articles within online news media. To do this, we train a DeBERTa-based synthetic news detector and classify over 15.90 million articles from 3,074 misinformation and mainstream news websites. We find that between January 1, 2022, and May 1, 2023, the relative number of synthetic news articles increased by 55.4% on mainstream websites while increasing by 457% on misinformation sites. We find that this increase is largely driven by smaller less popular websites. Analyzing the impact of the release of ChatGPT using an interrupted-time-series, we show that while its release resulted in a marked increase in synthetic articles on small sites as well as misinformation news websites, there was not a corresponding increase on large mainstream news websites.

翻译：随着ChatGPT等大规模语言模型（LLMs）的普及，越来越多的新闻网站开始利用其生成文章。然而，这些语言模型不仅可能为正规网站生成事实性错误的文章，声誉不佳的新闻网站更可利用LLMs批量制造虚假信息。为初步探究这一现象，我们开展了首批大规模研究，旨在评估合成文章在在线新闻媒体中的普遍程度。为此，我们训练了基于DeBERTa的合成新闻检测器，并对来自3074个虚假信息与主流新闻网站的超过1590万篇文章进行了分类。研究发现，在2022年1月1日至2023年5月1日期间，主流网站中合成新闻文章的相对数量增加了55.4%，而虚假信息网站则激增457%。分析表明，这一增长主要由规模较小、知名度较低的网站驱动。通过中断时间序列分析ChatGPT发布的影响，我们证明：其发布虽导致小型网站及虚假信息新闻网站的合成文章显著增加，但大型主流新闻网站并未出现相应增长。