Automatic Construction of Domain-Specific Sentiment Lexicons for Polarity Classification

Abstract

The article describes a strategy to build sentiment lexicons (positive and negative words) from corpora. Special attention will paid to the construction of a domain-specific lexicon from a corpus of movie reviews. Polarity words of the lexicon are assigned weights standing for different degrees of positiveness and negativeness. This lexicon is integrated into a sentiment analysis system in order to evaluate its performance in the task of sentiment classification. The experiments performed shows that the lexicon we generated automatically outperforms other manual lexicons when they are used as features of a supervised sentiment classifier.