Beautiful visualizations of how language differs among document types.
The Java Graphical Authorship Attribution Program
AI-writing humanizer for KO/EN/ZH/JA
Collected solutions from Google Code Jam programming competition (2008-2021).
Stylometry library for Burrows' Delta method
Stylometric Data Mining Library with a focus on identifying Satoshi Nakamoto as a case study.
Data and code for Kang et al., EMNLP 2019's paper titled "(Male, Bachelor) and (Female, Ph.D) have different connotations: Parallelly Annotated Stylistic Language Dataset with Multiple Personas"
Source code embeddings for various programming languages
Python package to deal with PAN corpora and extract stylometric features from text documents.
Interpretable stylometric profiling + author-style transfer built on explicit and LLM-genenated JSON fingerprints and local measurements. Fingerprint your corpus, inspect/visualize signals, then LLM-generate stylistically similar text with meaning preserved, deterministic post-processing, normalization controls, and deviation reports. CLI + API.
Write Like Me builds a voice profile from measurements of your writing. It supports multiple named voices, so one user can have separate profiles for professional writing, casual writing, and an admired author whose patterns they want to study.
A command-line tool for masking authorship of text, by changing the writing style with a Large Language Model.
QuitaUp: A tool for quantitative stylometric analysis
Measure how closely writing matches a learned author's style. Japanese & English, local-first CLI for LLMs and humans.
Ghost Writer — AI Content Engine with 40-point QA, 18 platform formatters, and triple-detector validation. Built on Ghost Protocol. Passes GPTZero, Pangram, and Originality.ai.
Bibtex copy of the Zotero bibliography on Stylometry
This project aims to address this gap by conducting a systematic, controlled study of human versus LLM-generated text detectability using paired question–answer datasets. Rather than proposing a novel detection architecture, the focus is on analyzing detection robustness, failure modes, and the impact of adversarial humanization strategies.
A tool that predicts the dialect of English of an SMS message using recurrent neural networks supplemented with data from Google Trends.
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