Glossary

Stylometry

Using quantitative features of writing style, such as word frequency and sentence length, to identify or compare authors.

Stylometry is the quantitative analysis of writing style, measuring features such as function-word frequency, sentence length, vocabulary richness, and punctuation habits, to identify, verify, or compare authors of a text. It treats style as a measurable fingerprint that persists across what a person writes, largely independent of subject matter.

The typical approach trains a statistical or machine-learning classification model on texts of known authorship and then applies it to a disputed text to see which known author's style it most resembles. This differs from distant reading, which studies thematic and historical patterns across a corpus, stylometry narrows in specifically on style markers for the purpose of attribution rather than on content or meaning.

Stylometry has been used in disputed-authorship cases, including historical debates over anonymous or jointly written works, as well as in plagiarism detection and forensic linguistics. It is one of the quantitative tools within cultural analytics. Common pitfalls include genre and translation effects that can shift style markers independently of authorship, unreliable results from very short texts, and overstating certainty, a stylometric match is evidence, not proof, and results are usually reported as probabilities rather than definitive attributions.

Last reviewed September 22, 2026

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Related terms

Distant reading Analyzing patterns across a large collection of texts computationally instead of closely reading each individual work. Classification A supervised learning task that assigns each input to one of a fixed set of discrete categories or labels. Cultural analytics Applying computational and statistical methods to large collections of cultural material to study patterns over time. Text Encoding Initiative (TEI) An XML standard for encoding literary and historical texts so their structure and scholarly annotations are machine-readable. Named Entity Recognition (NER) An NLP technique that locates and classifies names of people, organizations, places, and other entities within text.