This paper describes the participation of the Cross-genre Author Profiling System (CAPS) in the PAN16 shared task [15]. The classification system considers parts-of-speech, collocations, connective words and various other stylometric features to differentiate between the writing styles of male and female authors as well as between different age groups. The system achieves the second best score ...

In this paper we present the advantages of using an ontology service for the modelling of user profiles in the EC FP5 IST project NAMIC (IST-1999-12392). By means of an ontology server people set up user profiles, which are in fact views, i.e. specifications of queries on the ontology. These views are constructed using a JAVA API, which forms the commitment layer of the ontology, built on top o...

We describe the submission of the Sofia University team for the Author Profiling Task, part of the PAN 2015 Challenge. Given a set of writing samples by the same person, the task asks to predict some demographical information such as age and gender, as well as the personality type of that person. We experimented with SVM classifiers using variety of features extracted from publicly available re...

With the evolution of internet, author profiling has become a topic of great interest in the field of forensics, security, marketing, plagiarism detection etc. However the task of identifying the characteristics of the author just based on a text document has its own limitations and challenges. This paper reports on the design, techniques and learning models we adopted for the PAN-2014 Author P...

The objective of this work is to identify the gender and age of the author of a set of tweets using Support Vector Machines. This work is done as a task for the PAN 2016 which is a part of the CLEF conference. Techniques like tagging, removing stopwords, stemming, Bag-of-Words representation were used in order to create a 10 classes model. The tuning of the model was based on grid-search using ...

This paper describes and evaluates a supervised author profiling model. The suggested strategy can be adapted without any problem to various languages (such as Arabic, English, Spanish, and Portuguese). As features, we suggest using the m most frequent terms of the query text (isolated words and punctuation symbols with m at most 200). Applying a simple distance measure and looking at the neare...

This paper describes and evaluates an author profiling model called SPATIUM-L1. The suggested strategy can be adapted without any problem to different Indo-European languages (such as Dutch, English, and Spanish). As features, we suggest using the m most frequent terms of the query text (isolated words and punctuation symbols with m at most 200). Applying a simple distance measure and looking a...

In this paper we describe the participation of the Laboratory of Language Technologies of INAOE at PAN 2014. We address the Author Profiling (AP) task finding and exploiting relationships among terms, documents, profiles and subprofiles. Our approach uses the idea of second order attributes (a lowdimensional and dense document representation) [4], but goes beyond incorporating information among...

We describe our participation in the PAN 2017 shared task on Author Profiling, identifying authors’ gender and language variety for English, Spanish, Arabic and Portuguese. We describe both the final, submitted system, and a series of negative results. Our aim was to create a single model for both gender and language, and for all language varieties. Our best-performing system (on cross-validate...

In digital documents analysis for forensic applications, when anonymous documents are presented and it is not possible with the available tools to determine the true author of the document, there are of vital importance methods that identify the characteristics of the Author Profile (Gender, Age, Personality, etc.). We propose to use a simple method of classification based on the similarity bet...