Writing in the era of large language models: a bibliometric analysis of research field

The widespread adoption of large language models (LLMs) and chatbots over the past two years has significantly altered writing practices. This editorial paper aims to conduct a bibliometric analysis of the interdisciplinary research field concerning various aspects of writing in the context of LLMs. A search was conducted in the bibliographic database Scopus in December 2024 using the following query: (“large language model*” OR “LLM” OR “*GPT”) AND “writing”. We included studies published since 2020 and limited our search to articles, conference proceedings, books and book chapters. The search yielded a total of 1,629 documents. The retrieved records were analyzed using the R package bibliometrix and VOSviewer software. By employing these tools in combination, we identified the most relevant sources, leading countries and institutions, analyzed the most cited publications of the collection and constructed topical clusters. Our findings indicate that the most prominent research topics include the authorship and plagiarism in academic writing, challenges in second language education, automated writing evaluation, and issues related to creative writing in the context of LLMs. Keywords: Large language model; ChatGPT; Writing; Bibliometric review; bibliometrix R-package; VOSviewer; Scopus database; Keyword co-occurrence Acknowledgements: Tatiana A. Litvinova acknowledges the support of the Ministry of Education of the Russian Federation (the research was supported by the Ministry of Education of the Russian Federation within the framework of the state task in the field of science, topic number QRPK-2024-0011). Olga V. Dekhnich and G. Mikros received no financial support for the research, authorship, and publication of this article.