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Analysing the impact of ChatGPT in research
Halmstad University, School of Information Technology.ORCID iD: 0000-0002-0303-3858
Halmstad University, School of Information Technology.
2024 (English)In: Applied intelligence (Boston), ISSN 0924-669X, E-ISSN 1573-7497, Vol. 54, no 5, p. 4172-4188Article in journal (Refereed) Published
Abstract [en]

Large Language Models (LLMs) are a type of machine learning that handles a wide range of Natural Language Processing (NLP) scenarios. Recently, in December 2022, a company called OpenAI released ChatGPT, a tool that, within a few months, became the most representative example of LLMs, automatically generating unique and coherent text on many topics, summarising and rewriting it, or even translating it to other languages. ChatGPT originated some controversy in academia since students can generate unique text for writing assessments being sometimes extremely difficult to distinguish whether it comes from ChatGPT or a person. In research, some journals specifically banned ChatGPT in scientific papers. However, when used correctly, it becomes a powerful tool to rewrite, for instance, scientific papers and, thus, deliver researchers’ messages in a better way. In this paper, we conduct an empirical study of the impact of ChatGPT in research. We downloaded the abstract of over 45,000 papers from over 300 journals from Dec 2022 and Feb 2023 belonging to different research editorials. We use four of the most known ChatGPT detection tools and conclude that ChatGPT played a role in around 10% of the papers published in every editorial, showing that authors from different fields have rapidly adopted such a tool in their research. © The Author(s) 2024.

Place, publisher, year, edition, pages
New York, NY: Springer, 2024. Vol. 54, no 5, p. 4172-4188
Keywords [en]
ChatGPT, Large language models (LLMs), Natural language processing (NLP), Research
National Category
Natural Language Processing
Identifiers
URN: urn:nbn:se:hh:diva-53179DOI: 10.1007/s10489-024-05298-0ISI: 001190059700001Scopus ID: 2-s2.0-85188165139OAI: oai:DiVA.org:hh-53179DiVA, id: diva2:1851224
Funder
Halmstad University
Note

Funding: Open access funding provided by Halmstad University.

Available from: 2024-04-12 Created: 2024-04-12 Last updated: 2025-02-07Bibliographically approved

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Picazo-Sanchez, Pablo

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