Clasificación de polaridad en textos con opiniones en español mediante análisis sintáctico de dependencias


This article describes an opinion mining system that classifies the polarity of Spanish texts. We propose a nlp-based approach which performs segmentation, tokenization and pos tagging of texts to then obtain the syntactic structure of sentences by means of a dependency parser. The syntactic structure is then used to address three of the most significant linguistic constructions in the area in question: intensification, adversative subordinate clauses and negation. Experimental results show an improvement in performance with respect to purely lexical approaches and reinforce the idea that parsing is required to achieve a robust and reliable sentiment analysis system.

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@article{Vilares2013ClasificacinDP, title={Clasificaci{\'o}n de polaridad en textos con opiniones en espa{\~n}ol mediante an{\'a}lisis sint{\'a}ctico de dependencias}, author={David Vilares and Miguel A. Alonso and Carlos G{\'o}mez-Rodr{\'i}guez}, journal={Procesamiento del Lenguaje Natural}, year={2013}, volume={50}, pages={13-20} }