Unsupervised Authorship Attribution

Unsupervised Authorship Attribution is a methodological framework within computational stylometry that, without relying on prior labeled training data, identifies the likely authorship of textual documents by clustering or structuring unlabeled samples based on intrinsic stylistic patterns.

46

Publications

3.3K

Citations

109

Authors

58

Institutions

Publications per year

2017–2026

13

Authors

109

  1. MK
    Moshe Koppel

    Bar-Ilan University, Israel

    5 publications · 353 citations

    5

    h-index

  2. TS
    Thamar Solorio

    University of Houston, United States

    3 publications · 376 citations

    3

    h-index

  3. NA
    Navot Akiva

    Bar-Ilan University, Israel

    3 publications · 86 citations

    3

    h-index

  4. WA
    Waheed Anwar

    Islamia University of Bahawalpur, Pakistan

    2 publications · 61 citations

    2

    h-index

  5. HA
    Helen Ashman

    University of South Australia, Australia

    2 publications · 76 citations

    2

    h-index

1–5 of 109

Venues

  1. Literary and Linguistic Computing

    LLC · 3 publications · 272 citations

    3

    h-index

  2. 3

    h-index

  3. Neurocomputing

    2 publications · 38 citations

    2

    h-index

  4. 2

    h-index

  5. CLEF (Working Notes)

    1 publications · 12 citations

    2

    h-index

1–5