Stylometry
The statistical analysis of writing style — historically used for author identification.
Stylometry is the statistical analysis of writing style. Historically, it's been used to identify the authors of anonymous texts — disputed Shakespeare plays, the Federalist Papers, anonymous online posts. It analyzes features like average sentence length, function-word frequency, punctuation patterns, and vocabulary richness.
Stylometric features are some of the most stable signals available to AI detection. Even a careful prompt can't easily strip the statistical fingerprints of an LLM's training distribution. AI Detector API uses stylometric features alongside perplexity-based signals and classifier confidence.
The downside: stylometry can encode demographic or cultural patterns, so a detector that leans too heavily on it may show bias against non-native English speakers. We tune to minimize this — but no detector is perfectly neutral.
Related terms
- Burstiness— A measure of variation in sentence length, structure, and complexity across a piece of text.
- Perplexity— How surprised a language model is by a given piece of text — lower means the text looks more model-generated.
- AI detection— The task of identifying text that was written by a large language model rather than a human.
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