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From JGAAP

JGAAP (Java Graphical Authorship Attribution Program) is a Java-based, modular, program for textual analysis, text categorization, and authorship attribution i.e. stylometry / textometry. JGAAP is intended to tackle two different problems, firstly to allow people unfamiliar with machine learning and quantitative analysis the ability to use cutting edge techniques on their text based stylometry / textometry problems, and secondly to act as a framework for testing and comparing the effectiveness of different analytic techniques' performance on text analysis quickly and easily.

This wiki is a resource for everything there is to know about JGAAP. JGAAP is developed by the Evaluating Variation in Language Laboratory (EVL Lab) and released under the AGPLv3. We strive to keep this wiki and our website, evllabs.com, up-to-date with the most recent developments of the project and our research, if you have any trouble using JGAAP, would like to make a feature request, or want to contribute please contact any of the EVL Lab's staff.

Contents 1 News 2 Frequently Asked Questions 3 JGAAP Download 4 Project Documentation 5 Project Links 6 Further Reading 7 Project Team 7.1 Staff 7.2 Graduate Students 7.3 Undergrad Students 8 Project Funding 9 Project References

News

JGAAP version 5.3 is currently in the works and should be dropping in January. JGAAP 5.3 will have a number of backend updates and slight refactoring this will not include the removal of any methods or features you have come to use, however, you will find a number of methods has been deprecated and will be removed come the next major release 6.0. JGAAP 6.0 is planned for release mid-May, 2012.

If you have any feature requests or bugs to report please e-mail Michael Ryan

Frequently Asked Questions

FAQ List

JGAAP Download

You can downloaded the nightly build from our repository at GitHub here

The latest stable release src: JGAAP 5.2.0

All Stable releases are also available as a bundled jar: JGAAP 5.2.0 jar

You can also access all Prior Releases

Project Documentation

• JGAAP User Guide
• Documentation
• New User Tutorial (basic)
• New Developers
• Programmer's Guide
• Features
• Java Docs
  • JGAAP 5.2 API
  • JGAAP 5.1 API
  • JGAAP 5.0 API
  • JGAAP 4.x API

Project Links

• GitHub Repository
• GitHub Issue Tracker

Further Reading

You can see the underlying theory in Dr. Juola's monograph on Authorship Attribution (E-print). (2008)

A printed and bound version of this article is available at a 50% discount from NOW Publishers. This can be obtained by entering the promotional code INR001003 on the order form at NOW Publishers.

Project Team

Staff

• Patrick Juola
• John Noecker
• Michael Ryan
• Patrick Brennan

Graduate Students

• Darren Vescovi
• Amanda Kroft

Undergrad Students

• Mike Mehok
• Christine Gray
• Jeff Baker
• Adam Sargent

Project Funding

Funding for this project has been provided by the National Science Foundation, originally through award #OCI-0721667, and recently renewed via award #OCI-1032683.

(As always, the errors ours, the credit theirs.)

Project References

• Patrick Juola, John Sofko, and Patrick Brennan. (2006). "A Prototype for Authorship Attribution Studies" Literary and Linguistic Computing 21:169-178
• Patrick Juola and Harald Baayen. (2005). "A Controlled-Corpus Experiment in Authorship Identification by Cross-Entropy." Literary and Linguistic Computing , 20(Suppl 1) 59-67.
• Ad-hoc Authorship Attribution Competition Main Page
• Patrick Juola and John Sofko. (2004). "Proving and Improving Authorship Attribution." Proceedings of CaSTA-04 "The Face of Text."