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The diffusion of large language models in published academic articles.
1Department of Leadership, Higher and Adult Education, Ontario Institute for Studies in Education, Data, Equity and Policy in Education Lab, University of Toronto, Toronto, ON M5S 1V6.
Large language models (LLMs) are increasingly used in academic writing, with 57% of articles showing LLM influence by 2025. Adoption varies significantly by region, institution, publisher, and discipline, indicating a socially stratified trend in AI integration.
Area of Science:
- Scholarly communication and artificial intelligence impact on academic publishing.
Background:
- Large language models (LLMs) are transforming academic research practices.
- Questions arise regarding the adoption patterns and conditions of LLM use in scholarly work.
Purpose of the Study:
- To analyze the prevalence of LLM-associated language in academic articles.
- To identify social and institutional factors correlating with LLM adoption in research.
Main Methods:
- Analysis of 7.3 million full-text journal articles from 2020-2025 across four major publishers.
- Development of a focal word corpus to detect LLM-influenced text.
- Scoring articles based on focal word usage rates and applying difference-in-differences models.
Main Results:
- LLM influence detected in an estimated 57% of articles by 2025, up from 12% in 2023.
- Significant variations in LLM adoption across regions, institutional ranks, publishers, disciplines, and journal tiers.
- Economic development and English language proximity predict regional LLM adoption rates; lower-ranked institutions and younger publishers show higher adoption.
Conclusions:
- LLM adoption in academic writing is widespread but socially stratified.
- Understanding the social dynamics of LLM adoption is crucial for navigating the evolving relationship between AI and academic knowledge production.
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