# Exploring the change in scientific readability following the release of ChatGPT

arXiv: https://arxiv.org/abs/2506.21825 · HTML: https://mlsanity.com/paper/2506.21825/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 9 of its 42 references that are in the map.
- First posted on arXiv 26 Jun 2025.

## Builds on (most cited first, 9 of 9)

- [Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviews](https://mlsanity.com/paper/2403.07183/) (2024)
- [Mapping the Increasing Use of LLMs in Scientific Papers](https://mlsanity.com/paper/2404.01268/) (2024)
- [ChatGPT and a New Academic Reality: Artificial Intelligence-Written Research Papers and the Ethics of the Large Language Models in Scholarly Publishing](https://mlsanity.com/paper/2303.13367/) (2023)
- [Is ChatGPT Transforming Academics' Writing Style?](https://mlsanity.com/paper/2404.08627/) (2024)
- [ChatGPT as Research Scientist: Probing GPT's Capabilities as a Research Librarian, Research Ethicist, Data Generator and Data Predictor](https://mlsanity.com/paper/2406.14765/) (2024)
- [How many preprints have actually been printed and why: a case study of computer science preprints on arXiv](https://mlsanity.com/paper/2308.01899/) (2023)
- [Detection of ChatGPT Fake Science with the xFakeSci Learning Algorithm](https://mlsanity.com/paper/2308.11767/) (2023)
- [Incorrect Data in the Widely Used Inside Airbnb Dataset](https://mlsanity.com/paper/2007.03019/) (2020)
- [The role of geographic proximity in knowledge diffusion, measured by citations to scientific literature](https://mlsanity.com/paper/2002.00742/) (2020)

## Built on by (most cited first, 1 of 1)

- [Generative AI and the future of scientometrics: current topics and future questions](https://mlsanity.com/paper/2507.00783/) (2025)

## Abstract (arXiv)

The rise and growing popularity of accessible large language models have raised questions about their impact on various aspects of life, including how scientists write and publish their research. The primary objective of this paper is to analyze a dataset consisting of all abstracts posted on arXiv.org between 2010 and June 7th, 2024, to assess the evolution of their readability and determine whether significant shifts occurred following the release of ChatGPT in November 2022. Four standard readability formulas are used to calculate individual readability scores for each paper, classifying their level of readability. These scores are then aggregated by year and across the eight primary categories covered by the platform. The results show a steady annual decrease in readability, suggesting that abstracts are likely becoming increasingly complex. Additionally, following the release of ChatGPT, a significant change in readability is observed for 2023 and the analyzed months of 2024. Similar trends are found across categories, with most experiencing a notable change in readability during 2023 and 2024. These findings offer insights into the broader changes in readability and point to the likely influence of AI on scientific writing.