Supervised Authorship Attribution

Supervised Authorship Attribution is a machine learning approach within computational stylometry that, by leveraging labeled training data where texts are explicitly associated with known authors, trains predictive models to attribute authorship to unseen texts based on learned linguistic patterns distinguishing individual writers.

23

Publications

2.3K

Citations

69

Authors

40

Institutions

Publications per year

2017–2026

6

Authors

69

  1. ES
    Efstathios Stamatatos

    University of the Aegean, Greece

    2 publications · 1.4K citations

    2

    h-index

  2. MA
    Mahmoud Al‐Ayyoub

    Jordan University of Science and Technology, Jordan

    1 publications · 17 citations

    1

    h-index

  3. DH
    Daniel H. Solomon

    Brigham and Women's Hospital, United States

    1 publications · 12 citations

    1

    h-index

  4. LW
    Lingyu Wang

    Concordia University, Canada

    1 publications · 57 citations

    1

    h-index

  5. TQ
    Tieyun Qian

    Wuhan University, China

    1 publications · 13 citations

    1

    h-index

1–5 of 69

Venues

  1. Literary and Linguistic Computing

    LLC · 5 publications · 479 citations

    5

    h-index

  2. 2

    h-index

  3. International Journal of Web Information Systems

    IJWIS · 1 publications · 17 citations

    1

    h-index

  4. Neurocomputing

    1 publications · 13 citations

    1

    h-index

  5. 1

    h-index

1–5