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
Parents
23
1–5 of 23
69
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40

University of the Aegean
Mytilene, Greece
2 h-index
2 publications
1.4K citations

Heriot-Watt University
Edinburgh, United Kingdom
1 h-index
2 publications
20 citations

Chinese Academy of Sciences
Beijing, China
1 h-index
1 publications
13 citations
Harvard University
Cambridge, United States
1 h-index
1 publications
12 citations

Uniwersytet Komisji Edukacji Narodowej w Krakowie
Krakow, Poland
1 h-index
1 publications
58 citations

Radboud University Nijmegen
Nijmegen, The Netherlands
1 h-index
1 publications
16 citations
University of California, Irvine
Irvine, United States
1 h-index
2 publications
106 citations
Institute of Software
Beijing, China
1 h-index
1 publications
13 citations
1–8 of 40
LLC · 5 publications · 479 citations
5
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JASIST · 2 publications · 1.2K citations
2
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IJWIS · 1 publications · 17 citations
1
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1 publications · 13 citations
1
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1 publications · 224 citations
1
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1–5