  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 15.46 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 57.3% on mainstream websites while increasing by 474% 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.
