Using Verbs and Adjectives to Automatically Classify Blog Sentiment

Computational Approaches to Analyzing Weblogs

Volume

Papers from the 2006 AAAI Spring Symposium

Contents

This paper presents experiments on subjectivity and polarity classifications of topic- and genre-independent blog posts, making novel use of a linguistic feature, verb class information, and of an online resource, the Wikipedia dictionary, for determining the polarity of adjectives. Each post from a blog is classified as objective, positive, or negative. Our method of determining the polarity of adjectives has an accuracy rate of 90.9%. Accuracy rates of two verb classes demonstrating polarity are 89.3% and 91.2%. Initial classifier results show blog-post accuracies with significant increases above the established baseline classification.