Did ChatGPT or Copilot use alter the style of internet news headlines? A time series regression analysis
Not on the map. Why?
Abstract (arXiv)
The release of advanced Large Language Models (LLMs) such as ChatGPT and Copilot is changing the way text is created and may influence the content that we find on the web. This study investigated whether the release of these two popular LLMs coincided with a change in writing style in headlines and links on worldwide news websites. 175 NLP features were obtained for each text in a dataset of 451 million headlines/links. An interrupted time series analysis was applied for each of the 175 NLP features to evaluate whether there were any statistically significant sustained changes after the release dates of ChatGPT and/or Copilot. There were a total of 44 features that did not appear to have any significant sustained change after the release of ChatGPT/Copilot. A total of 91 other features did show significant change with ChatGPT and/or Copilot although significance with earlier control LLM release dates (GPT-1/2/3, Gopher) removed them from consideration. This initial analysis suggests these language models may have had a limited impact on the style of individual news headlines/links, with respect to only some NLP measures.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 7 of its 9 references that are in the map. First posted on arXiv 31 Mar 2025.
Builds on
7 of 9 references.
References · 7
- 2021All That's 'Human' Is Not Gold: Evaluating Human Evaluation of Generated Textcited by 287
- 2023Contrasting Linguistic Patterns in Human and LLM-Generated News Textcited by 62
- 2023Towards Understanding the Interplay of Generative Artificial Intelligence and the Internetcited by 54
- 2023A Survey on ChatGPT: AI-Generated Contents, Challenges, and Solutionscited by 35
- 2024The Rise of AI-Generated Content in Wikipediacited by 22
- 2024GPT-generated Text Detection: Benchmark Dataset and Tensor-based Detection Methodcited by 8
- 2024Interrupted time series analysis of clickbait on worldwide news websites, 2016-2023cited by 1
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Citing papers per year: 2025: 2.
2 papers.