On the Multilingual and Genre Robustness of EmoGraphs for Author Profiling in Social Media

Autores UPV
Año
Revista Lecture Notes in Computer Science

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.