On the Impact of Emotions on Author Profiling

Abstract

This is the author’s version of a work that was accepted for publication in Information Processing and Management. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Information Processing and Management 52 (2016) 73–92. DOI 10.1016/j.ipm.2015.06.003.[EN] In this paper, we investigate the impact of emotions on author profiling, concretely identifying age and gender. Firstly, we propose the EmoGraph method for modelling the way people use the language to express themselves on the basis of an emotion-labelled graph. We apply this representation model for identifying gender and age in the Spanish partition of the PAN-AP-13 corpus, obtaining comparable results to the best performing systems of the PAN Lab of CLEF. © 2015 Elsevier B.V. All rights reserved.The work of the first author was partially funded by Autoritas Consulting SA and by Spanish Ministry of Economics under grant ECOPORTUNITY IPT-2012-1220-430000. The work of the second author was carried out in the framework of the WIQ-EI IRSES project (Grant No. 269180) within the FP 7 Marie Curie, the DIANA APPLICATIONS: Finding Hidden Knowledge in Texts: Applications (TIN2012-38603-C02-01) project and the VLC/CAMPUS Microcluster on Multimodal Interaction in Intelligent Systems. A special mention to Maria Dolores Rangel Pardo for her linguistic contribution to this investigation.Rangel-Pardo, FM.; Rosso, P. (2016). On the Impact of Emotions on Author Profiling. Information Processing and Management. 52(1):73-92. https://doi.org/10.1016/j.ipm.2015.06.003S739252