We present the system we built for participating in the PAN-2016 Author Profiling Task [9]. The task asked to predict the gender and the age group of a person given several samples of his/her writing, and it was offered for three different languages: English, Spanish, and Dutch. We participated in both subtasks, for all three languages. Our approach focused on extracting genre-agnostic features...

In this paper, we focused on profiling authors on age, gender, and five personality traits. The corpus consists of anonymized twitter posts categorized into 4 different languages. Our proposed approach was to use a combination of tfidf, function words, stylistic features, and text bigrams, and used an SVM for each task.

This paper describes the participation of the Laboratory of Language Technologies of INAOE at PAN 2013 evaluation lab. We adopted second order representations for facing the problem of Author Profiling (AP). This representation tackles two shortcomings of the typical Bag-of-Terms: i) the sparsity and high dimensionality of document representations, and ii) the assumption of total independence b...

In this paper, we present a method for profiling the author of an anonymous text. Our approach is based on learning the author profile with a focus on dimensions age and gender. Our system takes as input a document which is written in English or in Spanish and generates the age and the gender of its author. First, we computed a ranked list of words that occur in the corpus and we grouped them i...

This paper describes the traditional authorship attribution subtask of the PAN/CLEF 2013 workshop. In our attempt to classify the documents based on gender and age of an author, we have applied a traditional approach of topic modeling using Latent Dirichlet Allocation[LDA]. We used the content based features like topics and style based features like preposition-frequencies, which act as the eff...

In this article we present a semantic-based approach concerning the identification of particular author’s traits, such as age and gender, from social media texts. The model here described is intended to provide information on different levels of analysis: from textual markers to semantics. Different classifiers were used to assess the performance and scope of the model.

Author profiling is the study of how language is shared by people, a problem of growing importance in applications dealing with security, in order to understand who could be behind an anonymous threat message, and marketing, where companies may be interested in knowing the demographics of people that in online reviews liked or disliked their products. In this talk we will give an overview of th...

We present the CIC’s approach to the Author Profiling (AP) task at PAN 2017. This year task consists of two subtasks: gender and language variety identification in English, Spanish, Portuguese, and Arabic. We use typed and untyped character n-grams, word n-grams, and non-textual features (domain names). We experimented with various feature representations (binary, raw frequency, normalized freq...

Department of Pharmacy, Uppsala University Drug Optimization and 11 Pharmaceutical Profiling Platform (UDOPP), Department of Pharmacy, 12 Uppsala University, Uppsala, Sweden 13 *Corresponding Author. Current address: Chemical Biology Consortium 14 Sweden, Science for Life Laboratory, Division of Translational Medicine and 15 Chemical Biology, Department of Medical Biochemistry 15 and Biophysics...