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Computational Intelligence and Neuroscience
Volume 2016, Article ID 1638936, 13 pages
http://dx.doi.org/10.1155/2016/1638936
Research Article

Improving Feature Representation Based on a Neural Network for Author Profiling in Social Media Texts

1Instituto Politécnico Nacional (IPN), Centro de Invetigación en Computación (CIC), Mexico City, Mexico
2Instituto Politécnico Nacional (IPN), Escuela Superior de Ingeniería Mecánica y Eléctrica Unidad Zacatenco (ESIME-Zacatenco), Mexico City, Mexico

Received 30 January 2016; Revised 19 July 2016; Accepted 14 August 2016

Academic Editor: Francesco Camastra

Copyright © 2016 Helena Gómez-Adorno et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

We introduce a lexical resource for preprocessing social media data. We show that a neural network-based feature representation is enhanced by using this resource. We conducted experiments on the PAN 2015 and PAN 2016 author profiling corpora and obtained better results when performing the data preprocessing using the developed lexical resource. The resource includes dictionaries of slang words, contractions, abbreviations, and emoticons commonly used in social media. Each of the dictionaries was built for the English, Spanish, Dutch, and Italian languages. The resource is freely available.