Examines how well ChatGPT mimics authors' writing styles using forensic text comparison methods, indicating challenges in accuracy.
This study examines ChatGPT’s ability to learn and replicate individuals’ unique writing styles. Using a one-shot training method, short texts from 300 authors of product reviews were used to train ChatGPT to generate new texts mimicking each author’s style. Likelihood ratio-based forensic text comparison experiments were conducted on same-author and different-author text pairs, involving human-written, machine-generated, and mixed texts. The findings indicate that replicating writing styles remains a significant challenge for ChatGPT. Linguistic analysis revealed that while both humans and machines exhibited preferred words and expressions, these preferences were more strongly associated with the machine.
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Shunichi Ishihara (2026) studied this question.
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