Scientific writing changes speed and style after ChatGPT launch
Accelerated Drift of Scientific Prose in the LLM Era: Evidence from an Interrupted Time-Series Analysis
Computation and LanguageArtificial Intelligence
Summary
Scientific papers follow writing trends that change slowly over time. This paper looks at how the release of ChatGPT in late 2022 sped up or altered those trends in scientific preprint abstracts. The authors found changes like longer words, less formula-like readability, and simpler sentence structures across several scientific fields. These shifts are complex and happen in different ways for different writing features, suggesting that scientific writing is evolving as a system beyond just the influence of large language models.
What this means in practice
- •For journal editors: Track evolving writing norms in submissions to adjust editing guidelines after LLM impacts on scientific prose.
- •For academic publishers: Develop metrics to monitor linguistic changes in manuscripts post-LLM release to maintain consistency and quality standards.
Authors
Hanna Hubarava, Benjamin V. Ineichen
Abstract
Every scientific text is embedded in the writing norms of its time: it reflects earlier publications while also shaping the texts that follow. The growing use of LLM-based writing tools introduces a new factor in this evolving system, but the linguistic changes coinciding with their emergence remain insufficiently understood. We investigate whether the trajectories of scientific-preprint writing changed in rate or direction after conversational LLMs became publicly accessible, using the release of ChatGPT in November 2022 as the observational breakpoint. We compare pre- and post-2022 trajectories across vocabulary, punctuation, readability, and syntax in abstracts from arXiv's artificial intelligence, statistics, and quantitative biology categories and from medRxiv. Using interrupted time-series regression, we find substantial post-2022 changes across multiple feature families and research domains, including increases in average word length, reduced formula-based readability, and declines in maximum dependency-tree depth and sentence-level depth variation. Individual features follow different dynamics: some lexical markers accelerate persistently, while others rise and then recede. Our findings show that isolated marker frequencies capture only part of the shift: changes in the rate, direction, and structure of linguistic trajectories provide complementary evidence of broader post-2022 change in scientific-preprint writing. More broadly, these findings motivate monitoring scientific writing as a multidimensional, evolving system rather than through a fixed set of LLM-associated markers.