Authorship Verification
31 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
Benchmarks
These leaderboards are used to track progress in Authorship Verification
Enron Emails
Most implemented papers
Explainable Authorship Verification in Social Media via Attention-based Similarity Learning
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.
Similarity Learning for Authorship Verification in Social Media
Authorship verification tries to answer the question if two documents with unknown authors were written by the same author or not.
GLAD: Groningen Lightweight Authorship Detection
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.
A Stylometric Inquiry into Hyperpartisan and Fake News
The articles originated from 9 well-known political publishers, 3 each from the mainstream, the hyperpartisan left-wing, and the hyperpartisan right-wing.
Authorship Attribution Using Text Distortion
A crucial point in this field is to quantify the personal style of writing, ideally in a way that is not affected by changes in topic or genre.
Authorship Attribution Using Text Distortion
A crucial point in this field is to quantify the personal style of writing, ideally in a way that is not affected by changes in topic or genre.
Authorship Verification based on Compression-Models
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.
Image Provenance Analysis at Scale
Given a large corpus of images and a query image, an interesting further step is to retrieve the set of original images whose content is present in the query image, as well as the detailed sequences of transformations that yield the query image given the original images.
Authorship verification in the absence of explicit features and thresholds
Moreover, many existing AV methods are based on explicit thresholds (needed to accept or reject a stated authorship), which are determined on training corpora.
Generalizing Unmasking for Short Texts
Authorship verification is the problem of inferring whether two texts were written by the same author.
