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Is ChatGPT Transforming Academics' Writing Style?

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arxiv 2404.08627 v2 pith:BCAJI7BD submitted 2024-04-12 cs.CL cs.AIcs.DLcs.LG

classification cs.CLcs.AIcs.DLcs.LG
keywords abstractsanalysischatgptstylewritingacademicsarxivfrequency
verification ladder T0 review T1 audit T2 compute T3 formal
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Based on one million arXiv papers submitted from May 2018 to January 2024, we assess the textual density of ChatGPT's writing style in their abstracts through a statistical analysis of word frequency changes. Our model is calibrated and validated on a mixture of real abstracts and ChatGPT-modified abstracts (simulated data) after a careful noise analysis. The words used for estimation are not fixed but adaptive, including those with decreasing frequency. We find that large language models (LLMs), represented by ChatGPT, are having an increasing impact on arXiv abstracts, especially in the field of computer science, where the fraction of LLM-style abstracts is estimated to be approximately 35%, if we take the responses of GPT-3.5 to one simple prompt, "revise the following sentences", as a baseline. We conclude with an analysis of both positive and negative aspects of the penetration of LLMs into academics' writing style.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Who Gets Seen in the Age of AI? Adoption Patterns of Large Language Models in Scholarly Writing and Citation Outcomes

    cs.CY 2025-09 reject novelty 5.0 of 10

    Analyzing 98,000 Scopus computer science papers, the paper finds a global rise in AI-like writing after ChatGPT and reports regional differences in citation returns, but the key differential-gain result is statistical...

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