A stylometric machine learning framework for authorship attribution of ChatGPT and student generated texts.

P M, Arulanandam A

DOI: 10.3389/frai.2026.1921847
Published: 2026
Container: Frontiers in artificial intelligence
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.3389/frai.2026.1921847,
  title = {A stylometric machine learning framework for authorship attribution of ChatGPT and student generated texts.},
  author = {P M and Arulanandam A},
  year = {2026},
  journal = {Frontiers in artificial intelligence},
  doi = {10.3389/frai.2026.1921847},
  url = {https://doi.org/10.3389/frai.2026.1921847}
}

RIS

TY  - JOUR
TI  - A stylometric machine learning framework for authorship attribution of ChatGPT and student generated texts.
AU  - P M
AU  - Arulanandam A
PY  - 2026
JO  - Frontiers in artificial intelligence
DO  - 10.3389/frai.2026.1921847
UR  - https://doi.org/10.3389/frai.2026.1921847
ER  -

APA

M, P., & A, A. (2026). A stylometric machine learning framework for authorship attribution of ChatGPT and student generated texts.. Frontiers in artificial intelligence. https://doi.org/10.3389/frai.2026.1921847

Source records

pubmed · retrieved 2026-09-25T10:43:02.228Z