USNA: A Dual-Classifier Approach to Contextual Sentiment Analysis

This paper describes a dual-classifier approach to contextual sentiment analysis at the SemEval-2013 Task 2. Contextual analysis of polarity focuses on a word or phrase, rather than the broader task of identifying the sentiment of an entire text. The Task 2 definition includes target word spans that range in size from a single word to entire sentences. However, the context of a single word is dependent on the word’s surrounding syntax, while a phrase contains most of the polarity within itself. We thus describe separate treatment with two independent classifiers, outperforming the accuracy of a single classifier. Our system ranked 6th out of 19 teams on SMS message classification, and 8th of 23 on twitter data. We also show a surprising result that a very small amount of word context is needed for high-performance polarity extraction.