Authorship attribution has always been a major issue. Although there are many up-and-running methods of relating an author or his writing traits through statistical text analysis, not all of them are accurate. Some of the most successful are based on quantitative text analysis.
JGAAP (short for Java Graphical Authorship Attribution Program) is a handy application that can be used for text analysis and authorship attribution, based on the study of stylometry and textometry.
Being a Java-based modular program, it will run on any computer with a version of Java installed on it.
Reliable authorship attribute database
JGAAP relies on an authorship attribute database in order find out who wrote a certain text. This is called “closed class” attribution. It heavily relies on the number of different author stylometric definitions, in order to provide you with an accurate answer.
This means that if you have ten authors in your database and you analyze a text, the application will relate the text to the author whose writing style it resembles the most, even if the text belongs to an author not found in the database. Thus, updating the database with various author stylometric attributes is the best way to ensure that any analysis of a text is precise and accurate.
A fast and powerful authoring tool
JGAAP enables you to check the authorship of a text, by comparing the statistical text analysis with the results existent in the applications database. It then determines the best possible matches for your text. You can also use it to test and compare the effectiveness of various text analysis techniques.
Furthermore, this application can be a dependable kickstarter for people unfamiliar with machine learning or any method of quantitative analysis, such as textometry or stylometry.