A statistical approach of distinguishing patent abstracts written by human from those generated by ChatGPT

A statistical approach of distinguishing patent abstracts written by human from those generated by ChatGPT

Journal article

1 volume.

This study investigates statistical differences between human-written patent abstracts and those generated by ChatGPT under controlled conditions. We analyze 500 patent abstracts from Taiwanese applications filed in 2020, a dataset selected to ensure temporal consistency and to minimize potential influence from AI-assisted writing tools. Given that patent abstracts emphasize essential technical features and follow relatively standardized, claim-oriented language, they provide a suitable setting for controlled stylistic analysis. Using restricted inputs (patent titles or original abstracts), we generate corresponding texts with ChatGPT and examine distributional differences via exploratory and confirmatory statistical analysis. The proposed framework, inspired by ecological diversity, models words and phrases as species and employs diversity-based metrics—such as standardized type-token ratio and entropy—as explanatory variables. Experimental results show that a small set of interpretable statistical features can achieve classification performance comparable to a BERT-based model, while requiring substantially fewer variables and lower computational cost. Importantly, the observed differences reflect distributional characteristics under constrained generation conditions rather than universal distinctions between human and AI-generated text. This study provides an interpretable, domain-specific baseline for understanding statistical differences between human and AI-generated language, highlighting the role of context, domain, and input constraints in shaping stylistic patterns.

Crossref

World Patent Information ; 85, June, 2026

World Patent Information

Oxford [England] : Elsevier Ltd., 2026.

English

https://www.sciencedirect.com/science/article/abs/pii/S0172219023000108

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