23 papers with code • 0 benchmarks • 2 datasets
Authorship verification (AV) is a research subject in the field of digital text forensics that concerns itself with the question, whether two documents have been written by the same person.
Definition taken from the paper Assessing the Applicability of Authorship Verification Methods, available at: https://arxiv.org/abs/1906.10551
These leaderboards are used to track progress in Authorship Verification
Authorship verification tries to answer the question if two documents with unknown authors were written by the same author or not.
Authorship verification is the task of analyzing the linguistic patterns of two or more texts to determine whether they were written by the same author or not.
We present a simple and effective approach to authorship verification for Dutch, English, Spanish and Greek, which can be easily ported to yet other languages. We train a binary linear classifier both on the features describing known and unknown documents individually, and on the joint features comparing these two types of documents.
The articles originated from 9 well-known political publishers, 3 each from the mainstream, the hyperpartisan left-wing, and the hyperpartisan right-wing.
Instead, the only three key components of our method are a compressing algorithm, a dissimilarity measure and a threshold, needed to accept or reject the authorship of the questioned document.
Moreover, many existing AV methods are based on explicit thresholds (needed to accept or reject a stated authorship), which are determined on training corpora.