Style based Authorship Attribution on English Editorial Documents

Style based Authorship Attribution on English Editorial Documents

The aim of the authorship attribution is identification of the author/s of unknown document(s). Every author has a unique style of writing pattern. The present paper identifies the unique style of an author(s) using lexical stylometric features. The lexical feature vectors of various authors are used in the supervised machine learning algorithms for predicting the unknown document. The highest ...

Authorship Attribution for Electronic Documents

Stylometric Authorship Attribution of Collaborative Documents

Stylometry is the study of writing style based on linguistic features and is typically applied to authorship attribution problems. In this work, we apply stylometry to a novel dataset of multi-authored documents collected from Wikia using both relaxed classification with a support vector machine (SVM) and multi-label classification techniques. We define five possible scenarios and show that one...

Experiments on authorship attribution by intertextual distance in English

How can it be said that texts are "near" or "distant" from one another? Are different texts by a single author more similar than texts by different authors? To answer these questions, a method is proposed by combination of the calculus of intertextual distance with automatic clustering and tree-classification. A blind test and some additional experiments show that this method offers an interest...

Recognizing and Imitating Programmer Style: Adversaries in Program Authorship Attribution

Source code attribution classifiers have recently become powerful. We consider the possibility that an adversary could craft code with the intention of causing a misclassification, i.e., creating a forgery of another author’s programming style in order to hide the forger’s own identity or blame the other author. We find that it is possible for a non-expert adversary to defeat such a system. In ...