Abstracted Identity: An Exploratory Corpus Analysis of AI’s Impact on Authorial Identity in Academic Writing
Abstract
Abstract Generative artificial intelligence is increasingly being used for academic writing. However, this is potentially a cause of concern if this is having an impact on how authors express themselves. In this study, I generate two corpora from the abstracts of academic articles in the ‘languages and linguistics’ field, one spanning 2018–2019 and another 2023–2024. To analyse these, I take a descriptive non-inferential corpus design to compare ngram frequency in the pre- and post-AI corpora to identify shifts in words and phrases related to authorial stance. I conclude by arguing that there is a possibility that generative AI is already influencing how abstracts are written, with a small shift away from authorial stance.
Fields of Study & Subjects
Discourse Analysis in Language Studies
Authorship Attribution and Profiling
Computational and Text Analysis Methods
Publication details
- Journal / source
- Digital studies in language and literature
- Publisher
- Walter de Gruyter GmbH
- Volume
- 3
- Issue
- 2
- Pages
- 213–245
- Publication date
- 20 April 2026
- Language
- EN