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

Mani P., Adaikalam Arulanandam

Open source

DOI: 10.3389/frai.2026.1921847
Published: 2026-08-24
Container: Frontiers in Artificial Intelligence
Publisher: Frontiers Media SA
Open access: unknown

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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 = {Mani P. and Adaikalam Arulanandam},
  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  - Mani P.
AU  - Adaikalam Arulanandam
PY  - 2026
JO  - Frontiers in Artificial Intelligence
DO  - 10.3389/frai.2026.1921847
UR  - https://doi.org/10.3389/frai.2026.1921847
ER  -

APA

P., M., & Arulanandam, 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

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crossref · retrieved 2026-11-06T01:51:52.147Z