The Author Profiling (AP) task aims to determine specific demographic characteristics such as gender and age, by analyzing the language usage in groups of authors. Notwithstanding the recent advances in AP, this is still an unsolved problem, especially in the case of social media domains. According to the literature most of the work has been devoted to the analysis of useful textual features. T...

In this paper we present our approach of solving the PAN 2016 Author Profiling Task. It involves classifying users’ gender and age using social media posts. We used SVM classifiers and neural networks on TF-IDF and verbosity features. Results showed that SVM classifiers are better for English datasets and neural networks perform better for Dutch and Spanish datasets.

In this paper we present an approach for the task of author profiling. We propose a coherent grouping of features combined with appropriate preprocessing steps for each group. The groups we used were stylometric and structural, featuring among others, trigrams and counts of twitter specific characteristics. We address gender and age prediction as a classification task and personality prediction...

In this paper, we describe the participation of the Language Technologies Lab of INAOE at PAN 2015. According to the Author Profiling (AP) literature. In this paper we take such discriminative and descriptive information into a new higher level exploiting a combination of discriminative and descriptive representations. For this we use dimensionality reduction techniques on the top of typical di...

In this work we are solving authorship attribution and author profiling tasks (by focusing on the age and gender dimensions) for the Lithuanian language. This paper reports the first results on literary texts, which we compared to the results, previously obtained with different functional styles and language types (i.e., parliamentary transcripts and forum posts). Using the Naïve Bayes Multinom...

This overview presents the framework and the results for the Author Profiling task at PAN 2014. Objective of this year is the analysis of the adaptability of the detection approaches when given different genres. For this purpose a corpus with four different parts (subcorpora) has been compiled: social media, Twitter, blogs, and hotel reviews. The construction of the Twitter subcorpus happened i...

The general goal of the author profiling task is to determine various social and demographic aspects of the author based on his pieces of writing. In this work, we propose an approach that combines word embeddings and classical logistic regression for identifying author gender and language variety based on the corresponding tweets. The model was trained on PAN 2017 Twitter Corpus that contains ...

Social media data allows researchers to establish relationships between everyday language and people’s sociodemographic variables, such as gender, age, language variety or personality. These variables configure social groups, where author profiling attempts to exploit the idea that they share a common language. This work describes our proposed method for the PAN 2017 Author Profiling shared tas...