In this paper, we present our approach for author profiling task based on Arabic content (Twitter case), which was one of the tasks required in PAN at CLEF 2017. Author profiling is the process of identifying authors’ traits, which constitute the profile of an author, by analysing his/her writings. In our research, we considered the gender and the variety (dialect) of an author as two important...

[This corrects the article on p. 96 in vol. 29, PMID: 27103964.].

Authorship analysis is a text analysis technique that is visualized mainly in three different techniques namely Authorship Profiling, Authorship Identification and Plagiarism Detection. In this paper a brief survey on the recent developments in the area of author profiling approaches were presented. Authorship Profiling is to ascertain various authors characteristics like age, gender, native co...

The author presents a brief discussion of criminal profiling followed by an introduction to the Italian Neural Network for Psychological Criminal Profiling (NNPCP) project. This project, based on a so-called neural network and data mining, is an innovative technique being developed with the intention of extending criminal profiling to single serious crimes through the use of a computerized data...

This paper describes a methodology proposed for author profiling using natural language processing and machine learning techniques. We used lexical information in the learning process. For those languages without lexicons, we automatically translated them, in order to be able to use this information. Finally, we will discuss how we applied this methodology to the 3rd Author Profiling Task at PA...

This paper presents a computational approach to author profiling taking gender and language variety into account. We apply an ensemble system with the output of multiple linear SVM classifiers trained on character and word ngrams. We evaluate the system using the dataset provided by the organizers of the 2017 PAN lab on author profiling. Our approach achieved 75% average accuracy on gender iden...

Author profiling is the problem of determining the characteristics of an author of an anonymous text. In this paper, we detail a method to determine the language variety and the gender of the authors of tweets, as a submission for the Author Profiling Task at PAN 2017. This method seeks to select the most significant character n-grams for each class considered, combining them with style feature...

This paper outlines the concepts and achievements of our evaluation lab on digital text forensics, PAN 13, which called for original research and development on plagiarism detection, author identification, and author profiling. We present a standardized evaluation framework for each of the three tasks and discuss the evaluation results of the altogether 58 submitted contributions. For the first...

This paper describes and evaluates a strategy for author profiling using TF-IDF and a Deep-Learning model based on Convolutional Neural Networks. We applied this strategy to the author profiling task of the PAN17 challenge and show that it can be applied to different languages (English, Spanish, Portuguese and Arabic). As features, we suggest using a simple cleaning method for both models, and ...