Relevance of the SFU ReviewSP-NEG corpus annotated with the scope of negation for supervised polarity classification in Spanish

Abstract

Up to now, negation is a challenging problem in the context of Sentiment Analysis. The study of negation implies the correct identification of negation markers, the scope and the interpretation of how negation affects the words that are within it, that is, whether it modifies their meaning or not and if so, whether it reverses, reduces or increments their polarity value. In addition, if we are interested in managing reviews in languages other than English, the issue becomes even more problematic due to the lack of resources. The present work shows the validity of the SFU ReviewSP-NEG corpus, which we annotated at negation level, for training supervised polarity classification systems in Spanish. The assessment has involved the comparison of different supervised models. The results achieved show the validity of the corpus and allow us to state that the annotation of how negation affects the words that are within its scope is important. Therefore, we propose to add a new phase to tackle negation in polarity classification systems (phase iii): i) identification of negation cues, ii) determination of the scope of negation, iii) identification of how negation affects the words that are within its scope, and iv) polarity classification taking into account negation.