Integrating Spanish Lexical Resources by Meta-classifiers for unsupervised polarity classification

In this paper we focus on unsupervised Sentiment Analysis in Spanish. The lack of resources for languages other than English, as for example Spanish, adds more complexity to the task. However, we should take advantage of some good already existing lexical resources. We have carried out several experiments using different unsupervised approaches in order to compare the different methodologies for solving the problem of the Spanish polarity classification in a corpus of movie reviews. Among all these approaches, perhaps the newest one integrates SentiWordNet with the Multilingual Central Repository to tackle the polarity detection directly over the Spanish corpus. However, the results obtained are not as promising as we expected, and so we have carried out another group of experiments combining all the methods by using meta-classifiers. The results obtained with stacking outperform the individual experiments and encourage us to continue in this way.

MARTÍNEZ-CÁMARA Eugenio;  MARTÍN-VALDIVIA M. Teresa;  MOLINA-GONZÁLEZ M. Dolores;  PEREA ORTEGA Jose Manuel; 

2014-09-01

SAGE PUBLICATIONS LTD

JRC89494

0165-5515,   

http://jis.sagepub.com/content/40/4/538,    https://publications.jrc.ec.europa.eu/repository/handle/JRC89494,   

10.1177/0165551514535710,