The PAN 2017 shared tasks on digital text forensics were held in conjunction with the
annual CLEF conference. This paper gives a high-level overview of each of the three shared …

Several authorship analysis tasks require the decomposition of a multiauthored text into its
authorial components. In this regard two basic prerequisites need to be addressed:(1) style …

Nowadays, social media like Twitter, Facebook, blogs, and LinkedIn are considered the
most used sources of information, while at the same time being the most visited and most …

Identifying academic plagiarism is a pressing problem, among others, for research
institutions, publishers, and funding organizations. Detection approaches proposed so far …

Authorship attribution (AA) is a very well studied research subject and the most prominent
subtask of authorship analysis. The goal of AA is to identify the most likely author of an …

The question of the authorship of texts has occupied numerous areas both within and
beyond research for a very long time. Knowing whether a particular person is a potential …

This paper presents a computational model for the unsupervised authorship attribution task
based on a traditional machine learning scheme. An improvement over the state of the art is …

Identifying the authorship either of an anonymous or a doubtful document constitutes a
cornerstone for automatic forensic applications. Moreover, it is a challenging task for both …

PAN 2018 explores several authorship analysis tasks enabling a systematic comparison of
competitive approaches and advancing research in digital text forensics. More specifically …