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A syntactic approach for opinion mining on Spanish reviews

Published online by Cambridge University Press:  09 August 2013

DAVID VILARES ,
MIGUEL A. ALONSO  and
CARLOS GÓMEZ-RODRÍGUEZ
DAVID VILARES
Affiliation:
Departamento de Computación, Universidade da Coruña Campus de Elviña, 15071 A Coruña, Spain e-mails: david.vilares@udc.es, miguel.alonso@udc.es, carlos.gomez@udc.es
MIGUEL A. ALONSO
Affiliation:
Departamento de Computación, Universidade da Coruña Campus de Elviña, 15071 A Coruña, Spain e-mails: david.vilares@udc.es, miguel.alonso@udc.es, carlos.gomez@udc.es
CARLOS GÓMEZ-RODRÍGUEZ
Affiliation:
Departamento de Computación, Universidade da Coruña Campus de Elviña, 15071 A Coruña, Spain e-mails: david.vilares@udc.es, miguel.alonso@udc.es, carlos.gomez@udc.es
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Abstract

We describe an opinion mining system which classifies the polarity of Spanish texts. We propose an NLP approach that undertakes pre-processing, tokenisation and POS tagging of texts to then obtain the syntactic structure of sentences by means of a dependency parser. This structure is then used to address three of the most significant linguistic constructions for the purpose in question: intensification, subordinate adversative clauses and negation. We also propose a semi-automatic domain adaptation method to improve the accuracy of our system in specific application domains, by enriching semantic dictionaries using machine learning methods in order to adapt the semantic orientation of their words to a particular field. Experimental results are promising in both general and specific domains.

Type
Articles
Information
Natural Language Engineering , Volume 21 , Issue 1 , January 2015 , pp. 139 - 163
Copyright
Copyright © Cambridge University Press 2013 

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