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Title: A Spanish Semantic Orientation Approach to Domain Adaptation for Polarity Classification
Authors: Molina González, M. Dolores
Martínez Cámara, Eugenio
Martín Valdivia, M. Teresa
Ureña López, L. Alfonso
Abstract: One of the problems of opinion mining is the domain adaptation of the sentiment classifiers. There are several approaches to tackling this problem. One of these is the integration of a list of opinion bearing words for the specific domain. This paper presents the generation of several resources for domain adaptation to polarity detection. On the other hand, the lack of resources in languages different from English has orientated our work towards developing sentiment lexicons for polarity classifiers in Spanish. The results show the validity of the new sentiment lexicons, which can be used as part of a polarity classifier.
Keywords: Spanish opinion mining
Sentiment lexicon
Domain adaptation
Issue Date: Jul-2015
Publisher: Elsevier
Citation: Molina-González, M. D., Martínez-Cámara, E., Martín-Valdivia, M. T., & Ureña-López, L. A. (2015). A Spanish semantic orientation approach to domain adaptation for polarity classification. Information Processing & Management, 51(4), 520-531.
Appears in Collections:DI-Artículos

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