Changes in Manuscript Length, Research Team Size, and International Collaboration in the Post-2022 Period: Evidence from PLOS ONE

Large language models (LLMs) have diffused rapidly into academic writing since late 2022. Using the complete population of 109,393 research articles published in $\mathit{\text{PLOS}}\mathit{\text{ONE}}$ between 2019 and 2025, we examine population-level structural publication indicators, including full-text manuscript length, authorship team size, reference volume, and cross-linguistic collaboration, before and after 2022. $\mathit{\text{PLOS}}\mathit{\text{ONE}}$'s multidisciplinary scope and consistent editorial framework allow cross-field comparison under uniform conditions over an extended period. Manuscript length increased substantially, with gains ranging from 14.8% among African-affiliated authors and 11.7% among Asian-affiliated authors to 5.3% among native English-speaking (NES) authors, cutting the word-count gap by 39%. More strikingly, non-native English-speaking (NNES) authors reduced both authorship team size, from 6.54 to 6.06 authors, or 7.3%, and collaboration with NES co-authors, from 17.8% to 12.2%, or 36%, while NES authors remained stable in both team size and collaboration rates. Reference counts increased modestly and uniformly across groups. These findings suggest that post-2022 tools may be reshaping not only how science is written, but who writes it together.