Building a fine-grained subjectivity lexicon from a web corpus

Abstract

In this paper we propose a method to build fine-grained subjectivity lexicons including nouns, verbs and adjectives. The method, which is applied for Dutch, is based on the comparison of word frequencies of three corpora: Wikipedia, News and News comments. Comparison of the corpora is carried out with two measures: log-likelihood ratio and a percentage difference calculation. The first step of the method involves subjectivity identification, i.e. determining if a word is subjective or not. The second step aims at the identification of more fine-grained subjectivity which is the distinction between actor subjectivity and speaker / writer subjectivity. The results suggest that this approach can be usefully applied producing subjectivity lexicons of high quality.