Abstract
Author profiling aims at identifying different traits such as age and gender of an author on the basis of her writings. We propose the novel EmoGraph graph-based approach where morphosyntactic categories are enriched with semantic and affective information. In this work we focus on testing the robustness of EmoGraphs when applied to age and gender identification. Results with PAN-AP-14 corpus show the competitiveness of the representation over genres and languages. Finally, some interesting insights are shown, for example with topic and emotion bounded genres such as hotel reviews.
The research has been carried out in the framework of the European Commission WIQ-EI IRSES (no. 269180) and DIANA - Finding Hidden Knowledge in Texts (TIN2012-38603-C02) projects. 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.
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Rangel, F., Rosso, P. (2015). On the Multilingual and Genre Robustness of EmoGraphs for Author Profiling in Social Media. In: Mothe, J., et al. Experimental IR Meets Multilinguality, Multimodality, and Interaction. CLEF 2015. Lecture Notes in Computer Science(), vol 9283. Springer, Cham. https://doi.org/10.1007/978-3-319-24027-5_28
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DOI: https://doi.org/10.1007/978-3-319-24027-5_28
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