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Background and Purpose: With the rapid advancements in generative AI, understanding its ability to emulate human language conventions is crucial. This work aims to analyze the possibility of applying AI technology in language production by comparing the lexico-grammatical features of abstracts created with the help of ChatGPT and written by British and American researchers. Methodology: Twenty papers written by researchers affiliated with UK universities and twenty by researchers affiliated with American universities were selected from the journals listed under the first quartile of the Web of Science and Scopus. Using the titles that were from the selected works, 40 abstracts were generated from ChatGPT for comparison. Each article was introduced with its title, and ChatGPT was asked to create an abstract based on the title. Subsequently, the subjects were examined with the help of Biber’s (1991) multivariate model considering five dimensions, which include the Informational vs Involved discourse, the Narrative vs Non-narrative, the Explicit vs. Situation- dependent discourse, Overt expression of argumentation/persuasion and the Impersonal/Abstract style as opposed to the Non-impersonal/Non-abstract style. Findings: The five factors analysed in the texts give evidence that ChatGPT generates more information-centric, non-narrative, argumentative, and less abstractive discourse than human researchers. Contributions: The results of the study show the possibilities for the further development of AI that helps to create language closer to human language. Keywords: Abstracts, ChatGPT, lexico-grammatical patterns, multidimensional analysis, research articles. Cite as: Ali, M., & Ali, S. (2024). Can artificial intelligence preferences be an alternative to human linguistic choices? A multidimensional analysis of research abstracts of English linguistics. Journal of Nusantara Studies, 9(2), 514-536. http://dx.doi.org/10.24200/jonus.vol9iss2pp514-536
Ali et al. (Wed,) studied this question.