We study the authorship attribution of documents given some prior stylistic characteristics of the author’s writing extracted from a corpus of known works, e.g., authentication of disputed documents or literary works. Although the pioneering paper based on word length histograms appeared at the very end of the nineteenth century, the resolution power of this and other stylometry approaches is y...

Children's attributions about story characters in ambiguous and unambiguous social situations were assessed. One hundred and forty-four 6-7-year-olds and 10-11-year-olds heard about actors who slighted a recipient intentionally or for an undetermined reason and then made causal attributions about the events, an emotion attribution about the recipient, and global personality attributions about t...

Authorship attribution can assist the criminal investigation procedure as well as cybercrime analysis. This task can be viewed as a single-label multi-class text categorization problem. Given that the style of a text can be represented as mere word frequencies selected in a language-independent method, suitable machine learning techniques able to deal with high dimensional feature spaces and sp...

Previous work has shown that the artist of an artwork can be identified by use of computational methods that analyse digital images. However, the digitised artworks are often investigated at a coarse scale discarding many of the important details that may define an artist’s style. In recent years high resolution images of artworks have become available, which, combined with increased processing...

The vast majority of previous studies in authorship attribution assume the existence of documents (or parts of documents) labeled by authorship to be used as training instances in either closed-set or open-set attribution. However, in several applications it is not easy or even possible to find such labeled data and it is necessary to build unsupervised attribution models that are able to estim...

Authorship attribution has a long history started since 19th century. Existing studies have used different sets of stylometric features and computational methodologies on a variety of corpus with different lengths and genres. This study presents a protocol to perform a systematic literature review (SLR) to identify the best combination of stylometric features and computational methodology. Spec...

Authorship attribution has been a persistent problem in the Classical genre, as texts that reach us from antiquity are often corrupted, edited, or forged over the thousands of years since their initial production. Scholars have worked on identifying writers’ stylistic differences in an attempt to distinguish genuine texts from fakes, and to attribute an author to previously anonymous works. Inc...

With the popularity of Internet technologies and applications, inappropriate or illegal online messages have become a problem for the society. The goal of authorship attribution for anonymous online messages is to identify the authorship from a group of potential suspects for investigation identification. Most previous contributions focused on extracting various writing-style features and emplo...

Authorship attribution and identifying time period of literary works are fundamental problems in quantitative analysis of languages. We investigate two fundamentally different machine learning text categorization methods, Support Vector Machines (SVM) and Naïve Bayes (NB), and several style markers in the categorization of Ottoman poems according to their poets and time periods. We use the coll...

A model of women's readiness to terminate an abusive relationship was examined, using cognitive and emotional factors to predict readiness to change as conceptualized in the transtheoretical model. Factors previously identified in the domestic violence literature were selected to represent cognitive predictors (attribution and attachment style) and affective predictors (depression, hopelessness...