Authorship attribution supported by statistical or computational methods has a long history
starting from the 19th century and is marked by the seminal study of Mosteller and Wallace …

Authorship identification is a task of identifying authors of anonymous texts given examples
of the writing of authors. The increasingly large volumes of anonymous texts on the Internet …

In this paper we will stress-test a recently proposed technique for computational authorship
verification,''unmasking'', which has been well received in the literature. The technique …

Keystroke and stylometry behavioral biometrics were investigated with the objective of
developing a robust system to authenticate students taking online examinations. This work …

Traditional approach Our approach authors small, closed set of authors large number of
authors data lots of data per author limited data results upper-90% exploratory experiments …

This paper describes the approach we took to create a machine learning model for the PAN
2021 Authorship Verification Task. The goal of this task is to predict if a given pair of …

The aim of this paper is to explore text topic influence in authorship attribution. Specifically,
we test the widely accepted belief that stylometric variables commonly used in authorship …

This paper describes the approach we took to create a machine learning model for the PAN
2020 Authorship Verification Task. For each document pair, we extracted stylometric …

This thesis describes work on the detection of anomalous material in text without the use of
training data. We use the term anomalous to refer to text that is irregular, or deviates …

This paper describes the approach we took to create a machine learning model for the PAN
2021 Style Change Detection Task. We approached this task by transforming it to an …