Machine learningStylometry

Authorship Attribution (Stylometry)

Authorship attribution is the task of identifying the most probable author of an anonymous or disputed text by analysing its stylistic fingerprint. Rooted in the statistical work of Mosteller and Wallace on the Federalist Papers (1964), the field was systematically surveyed and formalised by Stamatatos (2009), who catalogued feature sets ranging from character n-grams and function-word frequencies to syntactic and semantic representations used by modern machine-learning classifiers.

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Sources

  1. Stamatatos, E. (2009). A survey of modern authorship attribution methods. Journal of the American Society for Information Science and Technology, 60(3), 538–556. DOI: 10.1002/asi.21001

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Referenced by

ScholarGateAuthorship Attribution (Authorship Attribution (Stylometry)). Retrieved 2026-06-04 from https://scholargate.app/en/text-mining/authorship-attribution